Informative neural representations of unseen contents during higher-order processing in human brains and deep artificial networks A framework to pinpoint the scope of unconscious processing is critical to improve our models of visual consciousness. Previous research observed brain signatures of unconscious processing in visual cortex but these were not reliably identified. Further, whether unconscious content is represented in high-level stages of the ventral visual stream and linked parieto-frontal areas remains unknown. Using a within-subject, high-precision fMRI approach, we show that unconscious contents can be decoded from multivoxel patterns that are highly distributed alongside the ventral visual pathway and also involving parieto-frontal substrates. Classifiers trained with multivoxel patterns of conscious items generalised to predict the unconscious counterparts, indicating that their neural representations overlap. These findings suggest revisions to models of consciousness such as the neuronal global workspace. We then provide a computational simulation of visual processing/representation without perceptual sensitivity by using deep neural networks performing a similar visual task. The work provides a framework for pinpointing the representation of unconscious knowledge across different task domains.
Presynaptic Stochasticity Improves Energy Efficiency and Helps Alleviate the Stability-Plasticity Dilemma When an action potential arrives at a synapse there is a large probability that no neurotransmitter is released. Surprisingly, simple computational models suggest that these synaptic failures enable information processing at lower metabolic costs. However, these models only consider information transmission at single synapses ignoring the remainder of the neural network as well as its overall computational goal. Here, we investigate how synaptic failures affect the energy efficiency of models of entire neural networks that solve a goal-driven task. We find that presynaptic stochasticity and plasticity improve energy efficiency and show that the network allocates most energy to a sparse subset of important synapses. We demonstrate that stabilising these synapses helps to alleviate the stability-plasticity dilemma, thus connecting a presynaptic notion of importance to a computational role in lifelong learning. Overall, our findings present a set of hypotheses for how presynaptic plasticity and stochasticity contribute to sparsity, energy efficiency and improved trade-offs in the stability-plasticity dilemma.
Mitochondrial double-stranded RNAs as a pivotal mediator in the pathogenesis of Sjogrens syndrome ObjectiveSjogrens syndrome (SS) is a systemic autoimmune disease that targets the exocrine glands, resulting in impaired saliva and tear secretion. To date, type I interferons (I-IFNs) are increasingly recognized as pivotal mediators in SS, but their endogenous drivers have not been elucidated. This study investigates the role of mitochondrial double-stranded RNAs (mt-dsRNAs) in regulating I-IFN response in SS.

MethodsSaliva and tear from SS patients and controls (n=73 for saliva and n=16 for tear), the salivary glands of the SS-prone-non-obese-diabetic mouse, and primary human salivary glandular cells were screened for mt-dsRNAs by RT-qPCR. The human salivary cell line (NS-SV-AC) grown as three-dimensional spheroids were subject to dsRNA stress to measure mt-dsRNA induction and recapitulation of SS glandular inflammatory features. Acetylcholine, SS-IgG, upadacitinib (JAK1 inhibitor), or 2-C'-methyladenosine (mitochondrial transcription inhibitor) were applied to characterize the roles of mt-dsRNAs. To identify endogenous dsRNA-sensor and confirm the mitochondrial origin of cytoplasmic dsRNAs, the immunoprecipitation of dsRNAs was performed.

Resultsmt-dsRNAs were elevated in the SS specimens with salivary ND5 and tear CYTB1 being statistically associated with secretory dysfunction/inflammation and corneal/conjunctival damage, respectively. Stimulation of the spheroids with dsRNA stress of poly I:C induced mt-dsRNAs, p-PKR, and I-IFNS via the JAK1/STAT pathway whereas the inhibition of mt-RNA synthesis or JAK1 attenuated the glandular signature. The inhibitory effect of acetylcholine on mt-dsRNAs and I-IFNS induction was reversed by SS-IgG.

Conclusionmt-dsRNAs amplify the impact of dsRNA stress on SS glandular signatures in vitro, potentially propagating a pseudo-viral signal in the SS target tissue.

SummaryMitochondrial double-stranded RNA levels were elevated in the tear and saliva of SS patients, which was associated with secretory dysfunction and tissue inflammation. These RNAs amplified type I interferon signature as well as glandular phenotypes reported in SS. Inhibitors of mitochondrial RNA transcription or JAK1 in salivary gland acinar cell spheroids attenuated the mitochondrial RNA-mediated changes. EGFR inhibition leads to enhanced desmosome assembly and cohesion in cardiomyocytes The epidermal growth factor receptor (EGFR) is a ubiquitously expressed receptor tyrosine kinase, which is dysregulated in several kinds of cancer and heart diseases. Arrhythmogenic cardiomyopathy (AC) is a familial heart disease in part caused by impaired desmosome turnover. Thus, stabilization of desmosome integrity, may provide potential new treatment options. Desmosomes, apart from cellular cohesion, provide the structural framework of a signaling hub. Here, we investigated the role of EGFR inhibition on cardiomyocyte cohesion under physiological and pathophysiological conditions using the murine plakoglobin knockout AC model, in which EGFR was upregulated. EGFR inhibition led to enhanced cardiomyocyte cohesion. Immunoprecipitation showed an interaction of EGFR and desmoglein 2 (DSG2). Immunostaining and AFM revealed enhanced DSG2 localization and binding at cell borders upon EGFR inhibition. Enhanced area composita length and desmosome assembly were observed upon EGFR inhibition, confirmed by enhanced DSG2 and desmoplakin (DP) recruitment to cell borders. Thus, inhibiting EGFR, thereby stabilizing desmosome integrity, might provide new treatment options for AC.

SummaryShoykhet et al. show EGFR inhibition-enhanced cardiomyocyte cohesion. This positive adhesiotropy is achieved via an increase in desmosomal assembly and DP/DSG2 localization at cell borders and is the first step towards a novel therapeutic approach for arrhythmogenic cardiomyopathy. Conformist social learning leads to self-organised prevention against adverse bias in risky decision making Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majoritys behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This  collective behavioural rescue, emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective behavioural flexibility under conformist influences. G protein-coupled estrogen receptor activation by Bisphenol-A disrupts protection from apoptosis conferred by estrogen receptors ERα and ERβ in pancreatic beta cells 17{beta}-estradiol protects pancreatic {beta}-cells from apoptosis via the estrogen receptors ER, ER{beta} and GPER. Conversely, the endocrine disruptor Bisphenol-A (BPA), which exerts multiple effects in this cell type via the same estrogen receptors, increased basal apoptosis. The molecular initiated events that trigger these opposite actions have yet to be identified. We demonstrated that combined genetic downregulation and pharmacological blockade of each estrogen receptor increased apoptosis to a different extent. The increase in apoptosis induced by BPA was diminished by the pharmacological blockade or the genetic silencing of GPER, and it was partially reproduced by the GPER agonist G1. BPA and G1-induced apoptosis were abolished upon pharmacological inhibition, silencing of ER and ER{beta}, or in dispersed islet cells from ER{beta} knockout (BERKO) mice. Yet, the ER and ER{beta} agonists, PPT and DPN, respectively, had no effect on beta cell viability. To exert their biological actions, ER and ER{beta} form homodimers and heterodimers. Molecular dynamic simulations together with proximity ligand assay and coimmunoprecipitation experiments indicated that the interaction of BPA with ER and ER{beta} as well as the GPER activation by G1 decreased ER{beta} heterodimers. We propose that ER{beta} heterodimers play an antiapoptotic role in beta cells and that BPA- and G1-induced decrease in ER{beta} heterodimers leads to beta cell apoptosis. Unveiling how different estrogenic chemicals affect the crosstalk among estrogen receptors should help to identify diabetogenic endocrine disruptors.

HighlightsO_LIPharmacological blockade and gene silencing of estrogen receptors ER, ER{beta} and GPER indicate that they are antiapoptotic in basal conditions.
C_LIO_LIGPER activation by G1 and BPA triggered apoptosis via a crosstalk with ER and ER{beta}.
C_LIO_LIBPA interaction with ER and ER{beta} as well as GPER activation decreased ER{beta} heterodimers, which was associated to increased apoptosis.
C_LIO_LIThis pathway represents a novel molecular initiating event underlying the pro-apoptotic effect of BPA
C_LIO_LIThe EndoC-{beta}H1 cell line may be a valid model of human {beta}-cells for identifying diabetogenic pollutants.
C_LI DeepLIIF: Deep Learning-Inferred Multiplex ImmunoFluorescence for IHC Image Quantification Reporting biomarkers assessed by routine immunohistochemical (IHC) staining of tissue is broadly used in diagnostic pathology laboratories for patient care. To date, clinical reporting is predominantly qualitative or semi-quantitative. By creating a multitask deep learning framework referred to as DeepLIIF, we present a single-step solution to stain deconvolution/separation, cell segmentation, and quantitative single-cell IHC scoring. Leveraging a unique de novo dataset of co-registered IHC and multiplex immunofluorescence (mpIF) staining of the same slides, we segment and translate low-cost and prevalent IHC slides to more expensive-yet-informative mpIF images, while simultaneously providing the essential ground truth for the superimposed brightfield IHC channels. Moreover, a new nuclear-envelop stain, LAP2beta, with high (>95%) cell coverage is introduced to improve cell delineation/segmentation and protein expression quantification on IHC slides. By simultaneously translating input IHC images to clean/separated mpIF channels and performing cell segmentation/classification, we show that our model trained on clean IHC Ki67 data can generalize to more noisy and artifact-ridden images as well as other nuclear and non-nuclear markers such as CD3, CD8, BCL2, BCL6, MYC, MUM1, CD10, and TP53. We thoroughly evaluate our method on publicly available benchmark datasets as well as against pathologists semi-quantitative scoring. The code, the pre-trained models, along with easy-to-run containerized docker files as well as Google CoLab project are available at https://github.com/nadeemlab/deepliif. A tool for assessing alignment of biomedical data repositories with open, FAIR, citation and trustworthy principles Increasing attention is being paid to the operation of biomedical data repositories in light of efforts to improve how scientific data is handled and made available for the long term. Multiple groups have produced recommendations for functions that biomedical repositories should support, with many using requirements of the FAIR data principles as guidelines. However, FAIR is but one set of principles that has arisen out of the open science community. They are joined by principles governing open science, data citation and trustworthiness, all of which are important aspects for biomedical data repositories to support. Together, these define a framework for data repositories that we call OFCT: Open, FAIR, Citable and Trustworthy. Here we developed an instrument using the open source PolicyModels toolkit that attempts to operationalize key aspects of OFCT principles and piloted the instrument by evaluating eight biomedical community repositories listed by the NIDDK Information Network (dkNET.org). Repositories included both specialist repositories that focused on a particular data type or domain, in this case diabetes and metabolomics, and generalist repositories that accept all data types and domains. The goal of this work was both to obtain a sense of how much the design of current biomedical data repositories align with these principles and to augment the dkNET listing with additional information that may be important to investigators trying to choose a repository, e.g., does the repository fully support data citation? The evaluation was performed from March to November 2020 through inspection of documentation and interaction with the sites by the authors. Overall, although there was little explicit acknowledgement of any of the OFCT principles in our sample, the majority of repositories provided at least some support for their tenets. Second Heart Field-derived Cells Contribute to Angiotensin II-mediated Ascending Aortopathies BackgroundThe ascending aorta is a common location for aneurysm and dissection. This aortic region is populated by a mosaic of medial and adventitial cells that are embryonically derived from either the second heart field (SHF) or the cardiac neural crest. SHF-derived cells populate areas that coincide with the spatial specificity of thoracic aortopathies. The purpose of this study was to determine whether and how SHF-derived cells contribute to ascending aortopathies.

MethodsAscending aortic pathologies were examined in patients with sporadic thoracic aortopathies and angiotensin II (AngII)-infused mice. Ascending aortas without overt pathology from AngII-infused mice were subjected to mass spectrometry assisted proteomics, and molecular features of SHF-derived cells were determined by single cell transcriptomic analyses. Genetic deletion of either low-density lipoprotein receptor-related protein 1 (Lrp1) or transforming growth factor-{beta} receptor 2 (Tgfbr2) in SHF- derived cells was conducted to examine the impact of SHF-derived cells on vascular integrity.

ResultsPathologies in human ascending aortic aneurysmal tissues were predominant in outer medial layers and adventitia. This gradient was mimicked in mouse aortas following AngII infusion that was coincident with the distribution of SHF-derived cells. Proteomics indicated that brief AngII infusion, prior to overt pathology, evoked downregulation of SMC proteins and differential expression of extracellular matrix proteins, including several LRP1 ligands. LRP1 deletion in SHF-derived cells augmented AngII-induced ascending aortic aneurysm and rupture. Single cell transcriptomic analysis revealed that brief AngII infusion decreased Lrp1 and Tgfbr2 mRNA abundance in SHF-derived cells and induced a unique fibroblast population with low abundance of Tgfbr2 mRNA. SHF-specific Tgfbr2 deletion led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage. Integration of proteomic and single cell transcriptomics results identified plasminogen activator inhibitor 1 (PAI1) as the most increased protein in SHF-derived SMCs and fibroblasts during AngII infusion. Immunostaining revealed a transmural gradient of PAI1 in both ascending aortas of AngII-infused mice and human ascending aneurysmal aortas that mimicked the gradient of medial and adventitial pathologies.

ConclusionSHF-derived cells exert a critical role in maintaining vascular integrity through LRP1 and TGF-{beta} signaling associated with increases of aortic PAI1.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/930917v6_ufig1.gif" ALT="Figure 1">
View larger version (34K):
org.highwire.dtl.DTLVardef@185e3d9org.highwire.dtl.DTLVardef@131d702org.highwire.dtl.DTLVardef@11afa42org.highwire.dtl.DTLVardef@242786_HPS_FORMAT_FIGEXP  M_FIG C_FIG Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABS- SHF-derived SMCs and fibroblasts associate with AngII-induced aortic pathologies.
- AngII induces a distinct fibroblast sub-cluster that is less abundant for mRNAs related to major extracellular components and TGF{beta} ligands and receptors, but more abundant for proliferative genes.
- TGFBR2 deletion in SHF-derived cells are embryonic lethal with significant dilatation of the outflow tract in mice.
- SHF-specific deletion of LRP1 leads to aortic pathologies in mice, supporting the importance of SHF-derived cells in maintaining ascending aortic wall integrity.


What are the clinical implications?- Heterogeneity of the embryonic origins of SMCs and fibroblasts contributes to complex mechanisms of vasculopathy formation, which should be considered when investigating the pathogenesis of thoracic aortopathies. HYBRID REACTION-DIFFUSION AND CLOCK-AND-WAVEFRONT MODEL FOR THE ARREST OF OSCILLATIONS IN THE SOMITOGENESIS SEGMENTATION CLOCK AO_SCPLOWBSTRACTC_SCPLOWThe clock and wavefront paradigm is arguably the most widely accepted model for explaining the embryonic process of somitogenesis. According to this model, somitogenesis is based upon the interaction between a genetic oscillator, known as segmentation clock, and a differentiation wavefront, which provides the positional information indicating where each pair of somites is formed. Shortly after the clock and wavefront paradigm was introduced, Meinhardt presented a conceptually different mathematical model for morphogenesis in general, and somitogenesis in particular. Recently, Cotterell et al. rediscovered an equivalent model by systematically enumerating and studying small networks performing segmentation. Cotterell et al. called it a progressive oscillatory reaction-diffusion (PORD) model. In the Meinhardt-PORD model, somitogenesis is driven by short-range interactions and the posterior movement of the front is a local, emergent phenomenon, which is not controlled by global positional information. With this model, it is possible to explain some experimental observations that are incompatible with the clock and wavefront model. However the Meinhardt-PORD model has some important disadvantages of its own. Namely, it is quite sensitive to fluctuations and depends on very specific initial conditions (which are not biologically realistic). In this work, we propose an equivalent Meinhardt-PORD model, and then amend it to couple it with a wavefront consisting of a receding morphogen gradient. By doing so, we get a hybrid model between the Meinhardt-PORD and the clock-and-wavefront ones, which overcomes most of the deficiencies of the two originating models.

Somitogenesis, the process by which somites are formed, is an essential developmental stage in many vertebrates. This process occurs with a strikingly regular periodicity, that is preserved among embryos of a single species. The clock and wavefront paradigm is arguably the most widely accepted model for explaining somitogenesis. However, it is incapable of explaining some experimental facts, like the appearance of somites in the absence of an external wavefront (i.e. a receding morphogen gradient). Shortly after the clock and wavefront paradigm was introduced, Meinhardt presented a conceptually different mathematical model for morphogenesis in general, and somitogenesis in particular. Recently, Cotterell et al. rediscovered an equivalent model by systematically enumerating and studying small networks performing segmentation, and called it a progressive oscillatory reaction-diffusion (PORD) model. The Meinhardt-PORD model tackles some of the deficiencies of the clock and wave-front models, but it has some serious issues of its own. In the present work, we introduce an equivalent Meinhardt-PORD model, and then amend it to couple it with a receding morphogen gradient. By doing so, we get a hybrid model that incorporates characteristics of the Meinhardt-PORD and clock-and-wavefront models. We show that this hybrid model under-goes a bifurcation, from a stable to an unstable limit cycle, as the value of the parameter accounting for a background regulatory input (associated to the receding morphogen gradient) decreases. This bifurcation allows the model to explain why somites can form in the absence of an external wavefront, reassesses the role of the receding morphogen gradient as a conductor for somitogenesis, and makes the model behavior robust to random fluctuations, as well as independent from specific initial conditions (the latter, are two of the weak points of the Meinhardt-PORD model). We argue that this findings provide convincing evidence that reaction-diffusion and positional information (receding morphogen gradient) mechanisms could work together in somitogenesis. Applied tutorial for the design and fabrication of biomicrofluidic devices by resin 3D printing Stereolithographic (SL) 3D printing, especially digital light processing (DLP) printing, is a promising rapid fabrication method for bio-microfluidic applications such as clinical tests, lab-on-a-chip devices, and sensor integrated devices. The benefits of 3D printing lead many to believe this fabrication method will accelerate the use of microfluidics, but there are a number of potential obstacles to overcome for bioanalytical labs to fully utilize this technology. For commercially available printing materials, this includes challenges in producing prints with the print resolution and mechanical stability required for a particular design, along with cytotoxic components within many SL resins and low optical compatibility for imaging experiments. Potential solutions to these problems are scattered throughout the literature and rarely available in head-to-head comparisons. Therefore, we present here a concise guide to the principles of resin 3D printing most relevant for fabrication of bioanalytical microfluidic devices. Intended to quickly orient labs that are new to 3D printing, the tutorial includes the results of selected systematic tests to inform resin selection, strategies for design optimization, and improvement of biocompatibility of resin 3D printed bio-microfluidic devices. Inability to switch from ARID1A-BAF to ARID1B-BAF impairs exit from pluripotency and commitment towards neural crest formation in ARID1B-related neurodevelopmental disorders The BAF complex modulates chromatin accessibility. Specific BAF configurations have functional consequences, and subunit switches are essential for cell differentiation. ARID1B and its paralog ARID1A encode for mutually exclusive BAF subunits. De novo ARID1B haploinsufficient mutations cause a neurodevelopmental disorder spectrum, including Coffin-Siris syndrome, which is characterized by neurological and craniofacial features. Here, we reprogrammed ARID1B+/- Coffin-Siris patient-derived skin fibroblasts into iPSCs and modeled cranial neural crest cell (CNCC) formation. We discovered that ARID1B is active only during the first stage of this process, coinciding with neuroectoderm specification, where it is part of a lineage-specific BAF configuration (ARID1B-BAF), which includes SMARCA4 and nine additional subunits. ARID1B-BAF acts as a gatekeeper, ensuring exit from pluripotency and lineage commitment, by attenuating NANOG, SOX2 and thousands of enhancers directly regulated by these two pluripotency factors at the iPSC stage.

In iPSCs, these enhancers are maintained active by an ARID1A-containing BAF. At the onset of differentiation, cells transition from ARID1A-BAF to ARID1B-BAF, eliciting attenuation of the NANOG/SOX2 networks, and triggering pluripotency exit. Coffin-Siris patient cells fail to perform the ARID1A/ARID1B switch and maintain ARID1A-BAF at pluripotency enhancers throughout all stages of CNCC formation. This leads to a persistent and aberrant SOX2 and NANOG activity, which impairs CNCC formation. In fact, despite showing the typical neural crest signature (TFAP2A+, SOX9+), ARID1B-haploinsufficient CNCCs are also NANOG/OCT4-positive, in stark contrast with the ARID1B-wt CNCCs, which are NANOG/OCT4-negative.

These findings suggest a connection between ARID1B mutations, neuroectoderm formation, and a pathogenic mechanism for Coffin-Siris syndrome. Radiation-reprogrammed glioma stem cells generate vascular-like cells to build a trophic niche driving tumor recurrence Treatment-refractory glioma stem and tumor cells exhibit phenotypic plasticity driving recurrence, but the underlying molecular mechanisms remain to be elucidated. Here, we employed single-cell and whole transcriptomic analyses to discover that radiation induces a dynamic shift in functional states of glioma cells allowing for acquisition of vascular endothelial-like and pericyte-like cell phenotypes. These vascular-like cells provide a trophic niche to promote proliferation of irradiated glioma cells, and their selective depletion results in reduced tumor growth post-treatment in vivo. Mechanistically, the acquisition of vascular-like phenotype is driven by increased chromatin accessibility and H3K27 acetylation in specific vascular gene regions post-treatment. Blocking P300 histone acetyltransferase activity reverses the epigenetic changes induced by radiation, and inhibits the phenotypic transition and tumor growth. Our findings highlight an important role for P300 histone acetyltransferase in treatment-induced plasticity and opens a new therapeutic avenue for preventing glioma recurrence.

SignificanceOur study demonstrates that radiation therapy promotes glioma resistance by inducing vascular-like phenotypes in GSC that, in turn, aid in proliferation of the remaining tumor cells. This phenotype switch is mediated by P300 HAT, and inhibition of this enzyme is a potential therapeutic target for preventing glioma recurrence following radiation. Frequency modulated timer regulates mammalian hibernation Mammalian hibernators decrease basal metabolism and body temperature (Tb) to minimize energy expenditure in harsh seasons. During hibernation, Tb drops to low temperature (<10 {degrees}C) and remains constant for days, known as deep torpor in small mammalian hibernators. Spontaneous interbout arousals interrupt torpor bouts, when Tb recovers to euthermic state ~37 {degrees}C. Torpor-interbout arousal event repeats during several months of hibernation. However, little is known about mechanisms governing Tb fluctuation across torpor-interbout arousal cycles during hibernation. Recent improvement in data-logging techniques enables us to monitor Tb for more than hundred days with high precision, opening up new avenues for quantitative analysis to address the principle governing Tb fluctuation. Here, we analyzed Tb fluctuation across torpor-interbout arousal cycle of Syrian hamster, which can hibernate in response to chronic cold and short photoperiod under a laboratory condition, using generalized harmonic analysis and discovered a model with frequency modulation quantitatively reproducing Tb fluctuation. This analysis also identified an unexpectedly longer period of 120-430 days as the period that modulates another period of several days, generating Tb fluctuation for Syrian hamster. We propose that concerted action of two endogenous periods governs torpor-interbout arousal cycles during hibernation. Plant-host shift, spatial persistence, and the viability of an invasive insect population Assessing the effects of a plant-host shift is important for monitoring insect populations over long time periods and for interventions in a conservation or pest management framework. In a heterogeneous environment, individuals may disperse between sources and sinks in order to persist. Here we propose a single-species two-patch model that aims to capture the generational movement of an insect that exhibits density-dependent dispersal, to see how shifting between hosts could alter its viability and asymptotic dynamics. We then analyse the stability and persistence properties of the model and further validate it using parameter estimates derived from laboratory experiments. In order to evaluate the potential of this model, we applied it to Drosophila suzukii (Diptera: Drosophilidae), which has become a harmful pest in several countries around the world. Although many studies have investigated the preference and attractiveness of potential hosts on this invasive drosophilid, no studies thus far have investigated whether a shift of fruit host could affect such a species ecological viability or spatiotemporal persistence. The model results show that a shift in host choice can significantly affect the growth potential and fecundity of a species such as D. suzukii, which ultimately could aid such invasive populations in their ability to persist within a changing environment. Allosteric modulators enhance agonist efficacy by increasing the residence time of a GPCR in the active state Much hope in drug development comes from the discovery of positive allosteric modulators (PAM) that display target subtype selectivity, and act by increasing agonist potency and efficacy. How such compounds can allosterically influence agonist action remains unclear. Metabotropic glutamate receptors (mGlu) are G protein-coupled receptors that represent promising targets for brain diseases, and for which PAMs acting in the transmembrane domain have been developed. Here, we explore the effect of a PAM on the structural dynamics of mGlu2 in optimized detergent micelles using single molecule FRET at submillisecond timescales. We show that glutamate only partially stabilizes the extracellular domains in the active state. Full activation is only observed in the presence of a PAM or the Gi protein. Our results provide important insights on the role of allosteric modulators in mGlu activation, by stabilizing the active state of a receptor that is otherwise rapidly oscillating between active and inactive states. Correlational networking guides the discovery of cryptic natural product biosynthetic enzymes Bacterial natural product biosynthetic genes, canonically clustered, have been increasingly found to rely on cryptic enzymes encoded elsewhere in the genome for completion of biosynthesis. The study and application of lanthipeptides are frequently hindered by cryptic proteases required for final maturation. Here, we establish a global correlation network bridging the gap between lanthipeptide precursors and cryptic proteases. Applying our analysis to 161,954 bacterial genomes, we establish 5,209 correlations between precursors and cryptic proteases, with 91 prioritized. We use network predictions and co-expression analysis to reveal a previously missing protease for the maturation of class I lanthipeptide paenilan. We further discover widely distributed bacterial M16B metallopeptidases of previously unclear biological function as a new family of lanthipeptide proteases. We show the involvement of a pair of bifunctional M16B proteases in the production of novel class III lanthipeptides with high substrate specificity. Together, these results demonstrate the strength of our correlational networking approach to the discovery of cryptic lanthipeptide proteases and potentially other missing enzymes for natural products biosynthesis.

Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY The effect of recent habitat change on genetic diversity at putatively adaptive and neutral loci in Primula veris in semi-natural grasslands Recent habitat change in semi-natural grasslands due to a lack of management has been shown to affect the genetic diversity of grassland plants. However, it is unknown how a change in local environment affects genetic diversity at adaptive loci. We applied RADseq (restriction-site associated DNA sequencing) to extract > 3,000 SNPs across 568 individuals from 32 Estonian populations of Primula veris, a plant species common to semi-natural grasslands. We evaluated the effect of recent grassland overgrowth following management abandonment on the genetic diversity at putatively neutral and adaptive loci, which we distinguished by applying three methods, i.e., linear and categorical environmental association analyses, and an FST outlier test. For validation, we randomised the genotype to sample assignments. Effects of recent habitat change on genetic diversity differed between neutral and adaptive SNP sets. Genetic diversity assessed at putatively neutral loci was similar in open and overgrown habitats but showed a significant difference between these habitat types at putatively adaptive loci: overgrown (i.e. newly established) habitats exhibited higher genetic diversity at putatively adaptive loci than open (i.e. old) habitats, likely due to the exertion of novel selection pressures imposed by new habitat conditions. This increase in genetic diversity at putatively adaptive loci in the new environment points to currently ongoing selection processes where genetic adaptation to the old habitat is potentially lost through altered allele frequencies. Our study suggests that a recent change in local habitat conditions may not be reflected in neutral loci whereas putatively adaptive loci can inform about potential selection processes. Identification of age and ethnicity specific gene expression biomarkers for immune aging Human immune system functions over an entire lifetime, yet how and why the immune system becomes less effective with age are not well understood. Here, we characterize peripheral blood mononuclear cells transcriptome from 172 healthy adults with 21~90 years of age using RNA-seq and the weighted gene correlation network analyses (WGCNA). These data reveal a set of insightful gene expression modules and representative gene biomarkers for human immune system aging from Asian and Caucasian ancestry, respectively. Among them, the aging-specific modules show an age-related gene expression variation spike around early-seventies. In addition, it is not known whether Asian and Caucasian immune systems go through similar gene expression changes throughout their lifespan, and to what extent these aging-associated changes are shared among ethnicities. We find the top hub genes including NUDT7, CLPB, OXNAD1 and MLLT3 are shared between Asian and Caucasian aging related modules and further validated in human PBMCs from different age groups. Overall, the impact of age and race on transcriptional variation elucidated from this study provide insights into the transcriptional driver of immune aging. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Identification of druggable host targets needed for SARS-CoV-2 infection by combined pharmacological evaluation and cellular network directed prioritization both in vitro and in vivo. Identification of host factors contributing to replication of viruses and resulting disease progression remains a promising approach for development of new therapeutics. Here, we evaluated 6710 clinical and preclinical compounds targeting 2183 host proteins by immunocytofluorescence-based screening to identify SARS-CoV-2 infection inhibitors. Computationally integrating relationships between small molecule structure, dose-response antiviral activity, host target and cell interactome networking produced cellular networks important for infection. This analysis revealed 389 small molecules, >12 scaffold classes and 813 host targets with micromolar to low nanomolar activities. From these classes, representatives were extensively evaluated for mechanism of action in stable and primary human cell models, and additionally against Beta and Delta SARS-CoV-2 variants and MERS-CoV. One promising candidate, obatoclax, significantly reduced SARS-CoV-2 viral lung load in mice. Ultimately, this work establishes a rigorous approach for future pharmacological and computational identification of novel host factor dependencies and treatments for viral diseases. An Evolutionary Process Without Variation and Selection Natural selection successfully explains how organisms accumulate adaptive change despite that traits acquired over a lifetime are eliminated at the end of each generation. However, in some domains that exhibit cumulative, adaptive change--e.g., cultural evolution, and earliest life--acquired traits are retained; these domains do not face the problem that Darwins theory was designed to solve. Lack of transmission of acquired traits occurs when germ cells are protected from environmental change, due to a self-assembly code used in two distinct ways: (i) actively interpreted during development to generate a soma, and (ii) passively copied without interpretation during reproduction to generate germ cells. Early life and cultural evolution appear not to involve a self-assembly code used in these two ways. We suggest that cumulative, adaptive change in these domains is due to a lower-fidelity evolutionary process, and model it using Reflexively Autocatalytic and Foodset-generated networks. We refer to this more primitive evolutionary process as Self-Other Reorganisation (SOR) because it involves internal self-organising and self-maintaining processes within entities, as well as interaction between entities. SOR encompasses learning but in general operates across groups. We discuss the relationship between SOR and Lamarckism, and illustrate a special case of SOR without variation. Common variants in breast cancer risk loci predispose to distinct tumor subtypes BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.

MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.

ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at P<0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.

ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction. Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism-targeting as a promising antiviral strategy. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. Synthetic Cooling Agents in US-marketed E-cigarette Refill Liquids and Popular Disposable E-cigarettes: Chemical Analysis and Risk Assessment. BackgroundMenthol, through its cooling and pleasant sensory effects, facilitates smoking and tobacco product initiation, resulting in the high popularity of mint/menthol-flavored E-cigarettes. More recently, E-cigarette vendors started marketing synthetic cooling agents as additives that impart a cooling effect but lack a characteristic minty odor. Knowledge about content of synthetic coolants in US-marketed E-cigarette products and associated health risks is limited.

MethodsE-liquid vendor sites were searched with the terms "koolada", "kool/cool", "ice", or WS-3/WS-23, denoting individual cooling agents, and relevant refill E-liquids were purchased. "Ice" flavor varieties of Puffbar, the most popular disposable E-cigarette brand, were compared with non-"Ice" varieties. E-liquids were characterized, and synthetic coolants quantified using GC/MS. Margin of exposure (MOE), a risk assessment parameter, was calculated to assess the risk associated with synthetic coolant exposure from E-cigarette use.

ResultsWS-3 was detected in 24/25 refill E-liquids analyzed. All Puffbar flavor varieties contained either WS-23 (13/14) or WS-3 (5/14), in both "Ice"- and non-"Ice" flavors. Modeling consumption of WS-3 from vaped E-liquids, resulted in MOEs below the safe margin of 100 for most daily use scenarios. MOEs for WS-23 were <100 for 10/13 Puffbar flavors in all use scenarios. Puffbar power specifications are identical to Juul devices.

ConclusionsSynthetic cooling agents (WS-3/WS-23) were present in US-marketed E-cigarettes, at levels that may result in consumer exposures exceeding safety thresholds set by regulatory agencies. Synthetic coolants are not only found in mint-or menthol-flavored products, but also in fruit- and candy-flavored products, including popular disposable E-cigarette products such as Puffbar.

ImplicationsSynthetic cooling agents are widely used in "kool/cool"- and "ice"-flavored E-liquids and in E-liquids without these labels, both as a potential replacement for menthol or to add cooling  notes to non-menthol flavors. These agents may be used to bypass current and future regulatory limits on menthol content in tobacco products, and not just E-cigarettes. Since synthetic cooling agents are odorless, they may not fall under the category of "characterizing flavor", potentially circumventing regulatory measures based on this concept. Regulators need to consider the additional health risks associated with exposure to synthetic cooling agents.