Spatial organization of nuclear pores in Xenopus laevis oocytes Nuclear pores are protein assemblies inserted in the nuclear envelope of eukaryotic cells, acting as main gates for communication between nucleus and cytoplasm. So far, nuclear pores have been extensively studied to determine their structure and composition, yet their spatial organization and geometric arrangement on the nuclear surface are still poorly understood. Here, we analyze super-resolution images of the surface of Xenopus laevis oocyte nuclei during development, and characterize the arrangement of nuclear pores using tools commonly employed to study the atomic structural and topological features of soft matter. To interpret the experimental results, we hypothesize an effective interaction among nuclear pores and implemented it in extensive numerical simulations of octagonal clusters mimicking typical pore shapes. Thanks to our simple model, we find simulated spatial distributions of nuclear pores that are in excellent agreement with experiments, suggesting that an effective interaction among nuclear pores exists and could explain their geometrical arrangement. Furthermore, our results show that the statistical features of the geometric arrangement of nuclear pores do not depend on the type of pore-pore interaction, attractive or repulsive, but are mainly determined by the octagonal symmetry of each single pore. These results pave the way to further studies needed to determine the biological nature of pore-pore interactions.
Ear pinnae in a neotropical katydid function as ultrasound guides for bat call detection Early predator detection is a key component of the predator-prey arms race, and has driven the evolution of multiple animal hearing systems. Katydids (Insecta) have sophisticated ears, each consisting of paired tympana on each foreleg that receive sound directly externally, and internally via a narrowing ear canal through the acoustic spiracle. These ears are pressure-time difference receivers capable of sensitive and accurate directional hearing across a wide frequency range, despite the small size of katydids. Many katydid species have cuticular pinnae which form cavities around the outer tympanal surfaces, but their function is unknown. We investigated pinnal function in the katydid Copiphora gorgonensis by combining experimental biophysics and numerical modelling using 3D ear geometries. Results show that the pinnae in C. gorgonensis do not assist in directional hearing for specific call frequencies, but instead pinnae act as ultrasound detector devices. Pinnae induced large sound pressure gains that enhanced sound detection at high ultrasonic frequencies (> 60 kHz), matching the echolocation range of co-occurring insectivorous bats. Comparing pinnal mechanics of sympatric katydid species supports these findings, and suggests that pinnae evolved in katydids primarily for enhanced predator detection. Audiograms (both behavioural and neural) and tympanal cavity resonances obtained from living specimens corroborate our findings.
ModEst - Precise estimation of genome size from NGS data Precise estimates of genome sizes are important parameters for both theoretical and practical biodiversity genomics. We present here a fast, easy-to-implement and precise method to estimate genome size from the number of bases sequenced and the mean sequence coverage. To estimate the latter, we take advantage of the fact that a precise estimation of the Poisson distribution parameter lambda is possible from truncated data, restricted to the part of the coverage distribution representing the true underlying distribution. With simulations we could show that reasonable genome size estimates can be gained even from low-coverage (10X), highly discontinuous genome drafts. Comparison of estimates from a wide range of taxa and sequencing strategies with flow-cytometry estimates of the same individuals showed a very good fit and suggested that both methods yield comparable, interchangeable results. Extracellular Vesicle (EV) Mitochondria and EV/HSP27 Mixtures Protect the Ischemic Brain Endothelium Ischemic stroke causes brain endothelial cell (BEC) death and damages tight junction integrity of the blood-brain barrier (BBB). We harnessed the innate mitochondrial load of endothelial cell-derived extracellular vesicles (EVs) and utilized mixtures of EV/exogenous heat shock protein 27 (HSP27) as a one-two punch strategy to increase BEC survival (via EV mitochondria) and preserve their tight junction integrity (via HSP27 effects). We demonstrated that the medium-to-large (m/lEV) but not small EVs (sEV) transferred their mitochondrial load, which subsequently colocalized with the mitochondrial network of the recipient primary human BECs. BECs treated with m/lEVs increased relative ATP levels and displayed superior mitochondrial function. m/lEVs isolated from rotenone (mitochondrial complex I inhibitor) exposed BECs (RTN-m/lEVs) did not increase BECs ATP levels compared to naive m/lEVs. In contrast, RTN-sEVs functionality was minimally affected compared to naive sEVs. Compared to EV/HSP27 mixtures, PEG-DET/EV/HSP27 ternary mixtures increased HSP27 protein loading. (PEG-DET/HSP27)/EV ternary and EV/HSP27 binary mixtures decreased the paracellular permeability of small and large molecular mass fluorescent tracers in oxygen glucose-deprived primary human BECs. This one-two punch approach to increase BEC metabolic function and tight junction integrity is a promising strategy for BBB protection and prevention of long-term neurological dysfunction post-ischemic stroke.

Highlights[tpltrtarr] Medium-to-large extracellular vesicles (m/lEVs), not small EVs contain mitochondria
[tpltrtarr]m/lEVs increased ATP and mitochondrial function in brain endothelial cells (BECs)
[tpltrtarr]Donor m/lEV mitochondria colocalized with host mitochondria in recipient BECs
[tpltrtarr]m/lEVs from rotenone-exposed BECs did not increase recipient BEC ATP levels
[tpltrtarr]PEG-DET/EV/HSP27 ternary mixtures increase exogenous HSP27 protein loading


Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/466491v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@155f618org.highwire.dtl.DTLVardef@8fa778org.highwire.dtl.DTLVardef@13bd44aorg.highwire.dtl.DTLVardef@ee771e_HPS_FORMAT_FIGEXP  M_FIG C_FIG Neuronal Activation of the Gastrointestinal Tract Shapes the Gut Environment in Mice The enteric nervous system (ENS) coordinates responses that shape the intestinal milieu, and participates in bi-directional communication with various organs including the brain. Tools to study, and knowledge of, ENS development and function lag behind brain research. Herein, we deploy recombinant adeno-associated viral (rAAV) vectors with enhanced tropism for the gut to map and activate gut associated neurons in mice with spatial and temporal resolution. rAAV-mediated fluorescent labelling coupled with whole-tissue clearing methods in the small intestine and colon reveal novel neuronal architectures in the gut of mice. Viral delivery of genetically-encoded calcium indicators enable in vivo measurement of ENS activity. Further, we employed chemogentics to specifically activate gut neurons that express choline acetyltransferase (ChAT+) or tyrosine hydroxylase (TH+). Targeted activation of ChAT+ or TH+ neuronal populations associated with the gastrointestinal (GI) tract alters the intestinal transcriptome, mouse and microbial proteomes, metagenome, and fecal metabolome. We reveal previously unknown and broad roles for enteric neurons in modulating GI physiology, mucosal immunity, and microbiome structure, and provide evidence for novel functions by the ENS such as regulating fungal colonization and shaping of bile acid profiles in the gut. These advanced experimental tools and rich datasets with multi-parameter characterization of the gut ecosystem may facilitate expanded understanding and study of the ENS. Naming Human Diseases: Ethical Principles of Curating Exclusive Substitute for Inopportune Nosology BackgroundIn the medical sphere, understanding naming conventions strengthen the integrity of naming human diseases remains nominal rather than substantial yet. Since the current nosology-based standard for human diseases could not offer a one-size-fits-all corrective mechanism, many idiomatic but flawed names frequently appear in scientific literature and news outlets at the cost of sociocultural impacts.

ObjectiveWe attempt to examine the ethical oversights of current naming practices and propose heuristic rationales and approaches to determine a pithy name instead of an inopportune nosology.

MethodsFirst, we examined the compiled global online news volumes and emotional tones on some inopportune nosology like German measles, Middle Eastern Respiratory Syndrome, Spanish flu, Hong Kong flu, and Huntingtons disease in the wake of COVID-19. Second, we prototypically scrutinize the lexical dynamics and pathological differentials of German measles and common synonyms by leveraging the capacity of the Google Books Ngram Corpus. Third, we demonstrated the empirical approaches to curate an exclusive substitute for an anachronistic nosology German measles based on deep learning models and post-hoc explanations.

ResultsThe infodemiological study shows that the public informed the offensive names with extremely negative tones in textual and visual narratives. The findings of the historiographical study indicate that many synonyms of German measles did not survive, while German measles became an anachronistic usage, and rubella has taken the dominant place since 1994. The PubMedBERT model could identify rubella as a potential substitution for German measles with the highest semantic similarity. The results of the semantic drift experiments further indicate that rubella tends to survive during the ebb and flow of semantic drift.

ConclusionsOur findings indicate that the nosological evolution of anachronistic names could result in sociocultural impacts without a corrective mechanism. To mitigate such impacts, we introduce some ethical principles for formulating an improved naming scheme. Based on deep learning models and post-hoc explanations, our illustrated experiments could provide hallmark references to the remedial mechanism of naming practices and pertinent credit allocations. Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes IntroductionIncreasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. Sparseness leads to maximum likelihood estimators (MLEs) of log-OR parameters that are biased away from their null value of zero and tests with inflated type 1 errors. Different penalized-likelihood methods have been developed to mitigate sparse-data bias. We study penalized logistic regression using a class of log-F priors indexed by a shrinkage parameter m to shrink the biased MLE towards zero.

MethodsWe propose a two-step approach to the analysis of a genetic association study: first, a set of variants that show evidence of association with the trait is used to estimate m; and second, the estimated m is used for log-F -penalized logistic regression analyses of all variants using data augmentation with standard software. Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation.

ResultsWe evaluate the statistical properties of our proposed two-step method and compared its performance to other shrinkage methods by a simulation study. Our simulation studies suggest that the proposed log-F -penalized approach has lower bias and mean squared error than other methods considered. We also illustrate the approach on data from a study of genetic associations with "super senior" cases and middle aged controls.

Discussion/ConclusionWe have proposed a method for single rare variant analysis with binary phenotypes by logistic regression penalized by log-F priors. Our method has the advantage of being easily extended to correct for confounding due to population structure and genetic relatedness through a data augmentation approach. RNA-guided Cas12a and Cas9 knockout and knockin of the omega-1 locus of Schistosoma mansoni We compared the efficiency of gene knockout (KO) and precision of insertion (knock-in, KI) of the RNA-guided AsCas12a nuclease of Acidaminococcus sp. with that of SpCas9 from Streptococcus pyogenes, aiming to enhance the functional genomics toolkit for Schistosoma mansoni. Programmed DNA cleavages catalyzed by Cas12a and Cas9 result in staggered and blunt ended strand breaks, respectively. TTTV, the optimal protospacer adjacent motif for AsCas12a would occur frequently within the AT-rich genome of this platyhelminth. We deployed optimized conditions for the ratio of guide RNAs to the nuclease, donor templates, and electroporation parameters, to target a key enzyme termed omega-1 that is secreted by the schistosome egg. AsCas12a was more efficient than SpCas9 for gene knockout of omega-1 as determined by tracking of indels by decomposition (P < 0.001). Resulting from CRISPREsso2 analysis, most mutations were deletions; SpCas9 induced short deletions of 3 nt in length whereas AsCas12a induced deletions of 2 to 26 nt. Knockout efficiency of both nucleases markedly increased in the presence of short, single stranded oligodeoxynucleotide (ssODN) donor templates. With AsCas12a, ssODNs representative of both the non-CRISPR target (NT) and target (T) strands of the targeted gene were tested, resulting in KO efficiencies of 15.67, 28.71 and 21.43% in the SpCas9 plus donor ssODN, AsCas12a plus NT-ssODN, and AsCas12a plus T-ssODN groups, respectively. Trans cleavage activity against the ssODNs by activated AsCas12a was not apparent in vitro. Programmed SpCas9 editing led to more precise transgene insertion than AsCas12a, with KI efficiencies of 17.07% for the KI_SpCas9 group, 14.58% for KI_AsCas12a-NT-ssODN and 12.37% for KI_AsCas12a-T-ssODN. Although AsCas12a induced fewer mutations per genome than SpCas9, the phenotypic impact on transcription and expression of omega-1 was similar for both nucleases. These findings revealed that AsCas12a and SpCas9 both provide tractable routes for RNA-guided programmed mutation of the genome of the schistosome egg. Land use change through the lens of macroecology: insights from Azorean arthropods and the Maximum Entropy Theory of Ecology Human activity and land management practices, in particular land use change, have resulted in the global loss of biodiversity. These types of disturbance affect the shape of macroecological patterns, and therefore analyzing these patterns can provide insights into how ecosystems are affected by land use change. We here use arthropod census data from 96 sites at Terceira Island in the Azores archipelago across four different land uses of increasing management intensity: native forest, exotic forest, semi-natural pasture, and intensive pasture, to examine the effects of land use type on three macroecological patterns: the species abundance distribution, the metabolic rate distribution of individuals, and the species-area relationship. The Maximum Entropy Theory of Ecology (METE) has successfully predicted these patterns across habitats and taxa in undisturbed ecosystems, and thus provides a null expectation for their shapes. Across these patterns, we find that the forest habitats are the best fit by METE predictions, while the semi-natural pasture is consistently the worst fit, and the intensive pasture is intermediately well fit. We show that the direction of failure of the METE predictions at the pasture sites is likely due to the hyper-dominance of introduced spider species present there. We hypothesize that the particularly poor fit for the semi-natural pasture is due to the mix of arthropod communities out of equilibrium, leading to greater heterogeneity in composition and complex dynamics that violate METEs assumption of static state variables. The comparative better fit for the intensive pasture plausibly results from more homogeneous arthropod communities that are well adapted to intensive management, and thus whose state variables are less in flux. Analyzing deviations from theoretical predictions across land use type provides useful information about how land use and disturbance affect ecosystems, and such comparisons could be useful across other habitats and taxa. Genetically diverse mouse models of SARS-CoV-2 infection reproduce clinical variation and cytokine responses in COVID-19 Inflammation in response to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection drives severity of coronavirus disease 2019 (COVID-19), with effective versus dysregulated responses influenced by host genetics. To understand mechanisms of inflammation, animal models that reflect genetic diversity and clinical outcomes observed in humans are needed. We report a mouse panel comprising the diverse genetic backgrounds of the Collaborative Cross founder strains crossed to K18-hACE2 transgenic mice that confers high susceptibility to SARS-CoV-2. Infection of CC x K18-hACE2 F1 progeny resulted in a spectrum of weight loss, survival, viral replication kinetics, histopathology, and cytokine profiles, some of which were sex-specific. Importantly, survival was associated with early type I interferon (IFN) expression and a phased proinflammatory response distinct from mice with severe disease. Thus, dynamics of inflammatory responses observed in COVID-19 can be modeled in diverse mouse strains that provide a genetically tractable platform for understanding antiviral immunity and evaluating countermeasures.

One Sentence SummaryGenetically diverse mice display a broad spectrum of clinically relevant responses to SARS-CoV-2 infection, reflecting variability in COVID-19 disease. mTORC2 contributes to murine systemic autoimmunity The development of many systemic autoimmune diseases, including systemic lupus erythematosus, is associated with overactivation of the type I interferon (IFN) pathway, lymphopenia, and increased follicular helper T (Tfh) cell differentiation. However, the cellular and molecular mechanisms underlying these immunological perturbations remain incompletely understood. Here we show that the mechanistic target of rapamycin complex 2 (mTORC2) promotes Tfh differentiation and disrupts Treg homeostasis. Inactivation of mTORC2 in total T cells, but not in Tregs, greatly ameliorated the immunopathology in a systemic autoimmunity mouse model. This was associated with reduced Tfh differentiation, B cell activation, and reduced T cell glucose metabolism. Finally, we show that type I IFN can synergize with TCR ligation to activate mTORC2 in T cells, which partially contributes to T cell lymphopenia. These data indicate that mTORC2 may act as downstream of type I IFN, TCR, and costimulatory receptor ICOS, to promote glucose metabolism, Tfh differentiation, and T cell lymphopenia, but not to suppress Treg function in systemic autoimmunity. Our results suggest that mTORC2 might be a rational target for systemic autoimmunity treatment. Polycystins are upregulated in fibrotic kidneys and promote renal fibrosis Autosomal polycystic kidney disease (ADPKD) is caused by mutations in PKD1or PKD2 gene, which encodes polycystin-1 or polycystin-2 respectively. Paradoxically, polycystins are up-regulated in human ADPKD kidneys and overexpression of polycystin-1 even induced renal cyst formation in mice, suggesting that up-regulation of polycystin is pathogenic. In this study, we determined the role of polycystin in renal fibrosis and explored its underlying mechanisms. We found that the expression of polycystin-1 or polycystin-2 was positively correlated with the expression of collagen-I in the kidney of three different fibrotic mouse models. Pharmaceutical inhibition or genetic knockout of polycystin-2 reduced the expression of pro-fibrotic markers in fibrotic kidneys of two animal models. Moreover, conditional knockout of Pkd1 gene attenuated renal fibrosis in two mouse models. Enhancer of Zeste homolog 2 (EZH2) is a methyltransferase which plays important role in renal fibrosis. We found that EZH2 was positively correlated with the expression of polycystins in fibrotic kidneys. Conditional knockout of the Ezh2 attenuated the anti-fibrotic responses induced by Pkd1 deletion in fibrotic kidneys.

In conclusion, polycystins are up-regulated in injured kidneys and polycystins promote renal fibrosis through up-regulation of EZH2 in fibrotic kidneys, suggesting that renal fibrosis in polycystic kidneys is not the direct effect of PKD gene mutations.

SignificanceMutations of polycystins cause autosomal polycystic kidney disease (ADPKD) which is associated with increased renal fibrosis in cystic kidneys. However, the role of polycystin in renal fibrosis remains unclear. Here, we showed that the expression of polycystins is positively correlated with the development of renal fibrosis in injured kidneys. Pharmaceutical inhibition or genetic deletion of polycystin-2 attenuated renal fibrosis in fibrotic kidneys. Moreover, genetic deletion of polycystin-1 inhibited renal fibrosis in two different animal models. Finally, we showed that ablation of the methyltransferase EZH2 mitigated the anti-fibrotic effect of polycystin-1 deletion in fibrotic kidneys. We conclude that polycystin promotes through EZH2 and renal fibrosis in cystic kidney is not the direct effect of PKD gene mutations. Development and Characterization of PAR-Trackers: New Tools for Detecting Poly(ADP-ribose) In Vitro and In Vivo AO_SCPLOWBSTRACTC_SCPLOWADP-ribosylation (ADPRylation) is a reversible post-translation modification resulting in the covalent attachment of ADP-ribose (ADPR) moieties on substrate proteins. Naturally-occurring protein motifs and domains, including WWEs, PBZs, and macrodomains, act as "readers" for protein-linked ADPR. Although recombinant, antibody-like ADPR detection reagents containing these readers have facilitated the detection of ADPR, they are limited in their ability to capture the dynamic nature of ADPRylation. Herein, we describe and characterize a set of poly(ADP-ribose) (PAR) Trackers (PAR-Ts) - optimized dimerization-dependent or split-protein reassembly PAR sensors in which a naturally occurring PAR binding domain, WWE, was fused to both halves of dimerization-dependent GFP (ddGFP) or split Nano Luciferase (NanoLuc), respectively. We demonstrate that these new tools allow the detection and quantification of PAR levels in extracts, living cells, and living tissues with greater sensitivity, as well as temporal and spatial precision. Importantly, these sensors detect changes in cellular ADPR levels in response to physiological cues (e.g., hormone-dependent induction of adipogenesis without DNA damage), as well as xenograft tumor tissues in living mice. Our results indicate that PAR Trackers have broad utility for detecting ADPR in many different experimental and biological systems. Behavioural analysis of swarming mosquitoes reveals higher hearing sensitivity than previously measured with electrophysiology methods Mosquitoes of many species mate in station-keeping swarms. Mating chases ensue as soon as a male detects the flight tones of a female with his auditory organs. Previous studies of hearing thresholds have mainly used electrophysiological methods that prevent the mosquito from flying naturally. The main aim of this study was to quantify behaviourally the sound-level threshold at which males can hear females. Free-flying male Anopheles coluzzii were released in a large arena (~2 m high x 2 m x 1 m) with a conspicuous object on the ground that stimulates swarming behaviour. Males were exposed to a range of natural and synthetic played-back sounds of female flight. We monitored the responses of males and their distance to the speaker by recording changes in their wingbeat frequency and angular speed. We show that the mean male behavioural threshold of particle-velocity hearing lies between 13-20 dB SVL (95%-CI). A conservative estimate of 20 dB SVL (i.e., < 0.5 m/s particle velocity) is already 12 to 26 dB lower than most of the published electrophysiological measurements from the Johnstons organ. In addition, we suggest that 1) the first harmonic of female flight-sound is sufficient for males to detect her presence, 2) males respond with a greater amplitude to single-female sounds than to the sound of a group of females and 3) the response of males to the playback of the flight sound of a live female is the same as that of a recorded sound of constant frequency and amplitude. Aldh2 is a lineage-specific metabolic gatekeeper in melanocyte stem cells Melanocyte stem cells (McSCs) in zebrafish serve as an on-demand source of melanocytes during growth and regeneration, but metabolic programs associated with their activation and regenerative processes are not well known. Here, using live imaging coupled with scRNA-sequencing, we discovered that quiescent McSCs during regeneration activate a dormant embryonic neural crest transcriptional program followed by an aldehyde dehydrogenase (Aldh) 2 metabolic switch to generate progeny. Unexpectedly, while ALDH2 is well known for its aldehyde clearing mechanisms we find that in regenerating McSCs, Aldh2 activity is required to generate formate - the one-carbon (1C) building block for nucleotide biosynthesis - through formaldehyde metabolism. Consequently, we find that disrupting the 1C cycle with low-doses of methotrexate caused melanocyte regeneration defects. In the absence of Aldh2, we find that purines (but not pyrimidines) are the metabolic end product sufficient for activated McSCs to generate progeny. Together, our work reveals McSCs undergo a two-step cell state transition during regeneration, and that the reaction products of Aldh2 enzymes have tissue-specific stem cell functions that meet metabolic demands in regeneration.

SUMMARY STATEMENTIn melanocyte regeneration, quiescent McSCs respond by re-expressing a neural crest identity, followed by an Aldh2-dependent metabolic switch to generate progeny. Detecting phylodiversity-dependent diviersification with a general phylogenetic inference framework AO_SCPLOWBSTRACTC_SCPLOWDiversity-dependent diversification models have been extensively used to study the effect of ecological limits and feedback of community structure on species diversification processes, such as speciation and extinction. Current diversity-dependent diversification models characterise ecological limits by carrying capacities for species richness. Such ecological limits have been justified by niche filling arguments: as species diversity increases, the number of available niches for diversification decreases.

However, as species diversify they may diverge from one another phenotypically, which may open new niches for new species. Alternatively, this phenotypic divergence may not affect the species diversification process or even inhibit further diversification. Hence, it seems natural to explore the consequences of phylogenetic diversity-dependent (or phylodiversity-dependent) diversification. Current likelihood methods for estimating diversity-dependent diversification parameters cannot be used for this, as phylodiversity is continuously changing as time progresses and species form and become extinct.

Here, we present a new method based on Monte Carlo Expectation-Maximization (MCEM), designed to perform statistical inference on a general class of species diversification models and implemented in the R package emphasis. We use the method to fit phylodiversity-dependent diversification models to 14 phylogenies, and compare the results to the fit of a richness-dependent diversification model. We find that in a number of phylogenies, phylogenetic divergence indeed spurs speciation even though species richness reduces it. Not only do we thus shine a new light on diversity-dependent diversification, we also argue that our inference framework can handle a large class of diversification models for which currently no inference method exists. Deep learning: step forward to high-resolution in vivo shortwave infrared imaging Shortwave infrared window (SWIR: 1000-1700 nm) represents a major improvement compared to the NIR-I region (700-900 nm) in terms of temporal and spatial resolutions in depths down to 4 mm. SWIR is a fast and cheap alternative to more precise methods such as X-ray and opto-acoustic imaging. Main obstacles in SWIR imaging are the noise and scattering from tissues and skin that reduce the precision of the method. We demonstrate that the combination of SWIR in vivo imaging in the NIRIIb region (1500-1700 nm) with advanced deep learning image analysis allows to overcome these obstacles and making a large step forward to high resolution imaging: it allows to precisely segment vessels from tissues and noise, provides morphological structure of the vessels network, with learned pseudo-3D shape, their relative position, dynamic information of blood vascularization in depth in small animals and distinguish the vessels types: artieries and veins. For demonstration we use neural network IterNet that exploits structural redundancy of the blood vessels, which provides a useful analysis tool for raw SWIR images. Critical re-evaluation of the slope factor of the operational model of agonism Background and PurposeAlthough being a relative term, agonist efficacy is a cornerstone in the proper assessment of agonist selectivity and signalling bias. The operational model of agonism (OMA) has become successful in the determination of agonist efficacies and ranking them. In 1985, Black et al. introduced the slope factor to the OMA to make it more flexible and allow for fitting steep as well as flat concentration-response curves.

Experimental ApproachFunctional analysis of OMA demonstrates that the slope factor implemented by Black et al. affects relationships among parameters of the OMA, leading to wrong estimates of operational efficacy and affinity of an agonist. In contrast, functional analysis of OMA with Hill coefficient as a slope factor has not this flaw.

Key ResultsFitting of the OMA with Black et al. slope factor to concentration-response curves of several models (homotropic allosteric modulation, substrate inhibition and non-competitive auto-inhibition) gives wrong estimates of operational efficacy and affinity. In contrast, fitting of the OMA modified by the Hill coefficient to concentration-response curves of these several models gives correct estimates of operational efficacy and affinity.

Conclusion and ImplicationsThe OMA modified by the Hill coefficient can be used for correct ranking of agonism and subsequent analysis, like quantification of signalling bias. Inferring the neural basis of binaural phenomena with a modified autoencoder Broad organizational features of the auditory pathway have been replicated by artificial neural networks trained on diverse and naturalistic stimuli. It is credible that neural network analogues could also reveal specific neural computations underlying targeted auditory phenomena. This remains to be established. Here, we examined a modified autoencoder (a deep neural network akin to symbolic regression) trained to imitate an auditory behavior rooted in the binaural system. The behavior promoted the use of split-second interaural timing cues to improve the detection of a tone presented in noise. In the optimal network, we observed the emergence of specialized computations with prominent similarities to animal models. Artificial neurons developed a sensitivity to temporal delays that increased deeper into the network and were widely distributed in preference (extending to delays beyond the range permitted by head width), and the ensuing dynamics were consistent with a binaural cross-correlation mechanism. Our results attest to the generality of these solutions for performing signal detection at low frequencies. Moreover, this is a primary demonstration that deep learning methods can be used to infer tangible mechanisms underlying auditory perception.

AUTHOR SUMMARYDo artificial intelligence (AI) systems process sounds in a similar way to the brain? If so, they represent a vital resource with which to investigate sensory systems. Here, we report an AI system that automatically developed auditory computations similar to those described in animal neurophysiology. The network learnt to use subtle discrepancies across its "two ears" to better detect a signal amongst a background noise. In the process, tuning to timing cues and established mechanisms of binaural hearing (relating to the use of both ears) developed internally. The results offer insight into computations occurring in deep brain structures that are difficult to measure with non-invasive techniques. Further, the results endorse informed associations made between AI systems and the auditory brain. First evidence of in vitro cytotoxic effects of marine microlitter on Merluccius merluccius and Mullus barbatus, two Mediterranean commercial fish species Marine litter is composed mainly of plastics and is recognized as a serious threats to marine ecosystems. Ecotoxicological approaches have started elucidating the potential severity of microplastics (MPs) in controlled laboratory studies with pristine materials but no information exist on marine environmental microlitter as a whole. Here, we characterized the litter in the coastal Northern Tyrrhenian sea and in the stomach of two fish species of socio-economic importance, and exposed primary cell cultures of mucosal and lymphoid organs to marine microlitter for evaluating possible cytotoxic effects. An average of 0.30 {+/-} 0.02 microlitter items m-3 was found in water samples. FT-IR analysis revealed that plastic particles, namely HDPE, polyamide and polypropylene were present in 100% and 83.3% of Merluccius merluccius and Mullus barbatus analyzed, which overall ingested 14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual, respectively. Moreover, microlitter was confirmed as a vector of microorganisms. Lastly, the apical end-point of viability was found to be significantly reduced in splenic cells exposed in vitro to two microlitter conditions. Considering the role of the spleen in the mounting of adaptive immune responses, our results warrant more in-depth investigations for clarifying the actual susceptibility of these two species to anthropogenic microlitter.

HighlightsO_LI0.30 {+/-} 0.02 microlitter items m-3 were found at the surface of coastal Northern Tyrrhenian sea
C_LIO_LI14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual were retrieved from the stomach of hakes and mullets
C_LIO_LIThe ingested microlitter contained plastic items
C_LIO_LIMicrolitter was validated as a carrier of bacteria, fungi and flagellates
C_LIO_LISplenic cells exposed to two microlitter conditions for 72 hours suffered cytotoxicity
C_LI A novel Boolean network inference strategy to model early hematopoiesis aging Hematopoietic stem cell (HSC) aging is a multifactorial event that leads to changes in HSC properties and function. These changes are intrinsically coordinated and affect the early hematopoiesis, involving hematopoietic stem and progenitor cells (HSPCs). The objective of this work is to better understand the mechanisms and factors controlling these changes. We have therefore developed an original strategy to construct a Boolean network of genes explaining the priming and homeostasis of HSCs (graphical abstract). Based on our previous scRNA-seq data, we performed an exhaustive analysis of the transcriptional network and identified active transcription modules or regulons along the differentiation trajectory of selected HSPC states. This global view of transcriptional regulation led us to focus on 15 components, 13 selected TFs (Tal1, Fli1, Gata2, Gata1, Zfpm1, Egr1, Junb, Ikzf1, Myc, Cebpa, Bclaf1, Klf1, Spi1) and 2 complexes regulating the ability of HSC to cycle (CDK4/6 - Cyclin D and CIP/KIP). We then defined the connections controlling the differentiation dynamics of HSC states and constructed an influence graph between the TFs involved in the dynamics by mixing observations from our scRNA-seq data and knowledge from the literature. Then, using answer set programming (ASP) and in silico perturbation analysis, we obtained a Boolean model which is the solution of a Boolean satisfiability problem. Finally, perturbation of the model based on age-related changes revealed important regulations, such as the overactivation of Egr1 and Junb or the loss of Cebpa activation by Gata2, which were found to be relevant for the myeloid bias of aged HSC. Our work shows the efficiency of the combination of manual and systematic methods to elaborate a Boolean model. The developed strategy led to the proposal of new regulatory mechanisms underlying the differentiation bias of aged HSCs, explaining the decreased transcriptional priming of HSCs to all mature cell types except megakaryocytes. SARS-CoV-2 Beta Variant Substitutions Alter Spike Glycoprotein Receptor Binding Domain Structure and Stability The emergence of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) and the subsequent COVID-19 pandemic has visited a terrible cost on the world in the forms of disease, death, and economic turmoil. The rapid development and deployment of extremely effective vaccines against SARS-CoV-2 have seemingly brought within reach the end of the pandemic. However, the virus has acquired mutations; and emerging variants of concern (VOC) are more infectious and reduce the efficacy of existing vaccines. While promising efforts to combat these variants are underway, the evolutionary pressures leading to these variants are poorly understood. To that end, here we have studied the effects on the structure and function of the SARS-CoV-2 spike glycoprotein receptor-binding domain of three amino-acid substitutions found in several variants of concern, including alpha (B.1.1.7), beta (B.1.351), and gamma (P.1). We found that these substitutions alter the RBD structure, stability, and ability to bind to ACE2, in such a way as to possibly have opposing and compensatory effects. These findings provide new insights into how these VOC may have been selected for infectivity while maintaining the structure and stability of the receptor binding domain. 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. A Neurogenic Signature Involving Monoamine Oxidase-A controls Human Thermogenic Adipose Tissue Development Mechanisms that control "beige/brite" thermogenic adipose tissue development may be harnessed to improve human metabolic health. To define these mechanisms, we developed a species-hybrid model in which human mesenchymal progenitor cells were used to develop white or thermogenic/beige adipose tissue in mice. The hybrid adipose tissue developed distinctive features of human adipose tissue, such as larger adipocyte size, despite its neurovascular architecture being entirely of murine origin. Thermogenic adipose tissue recruited a denser, qualitatively distinct vascular network, differing in genes mapping to circadian rhythm pathways, and denser sympathetic innervation. The enhanced thermogenic neurovascular network was associated with human adipocyte expression of THBS4, TNC, NTRK3 and SPARCL1, which enhance neurogenesis, and decreased expression of MAOA and ACHE, which control neurotransmitter tone. Systemic inhibition of MAOA, which is present in human but absent in mouse adipocytes, induced browning of human but not mouse adipose tissue, revealing the physiological relevance of this pathway. Our results reveal species-specific cell type dependencies controlling the development of thermogenic adipose tissue and point to human adipocyte MAOA as a potential target for metabolic disease therapy. Spatial control of cell division by GA-OsGRF7/8 module in a leaf explains the leaf length variation between cultivated and wild rice O_LICellular and genetic understanding of rice leaf size regulation is limited, despite rice being the staple food of more than half of the global population. We investigated the mechanism controlling the rice leaf length using cultivated and wild rice accessions that remarkably differed for leaf size.
C_LIO_LIComparative transcriptomics, Gibberellic Acid (GA) quantification, and leaf kinematics of the contrasting accessions suggested the involvement of GA, cell cycle, and Growth-Regulating Factors (GRFs) in the rice leaf size regulation. Zone-specific expression analysis and VIGS established the functions of specific GRFs in the process.
C_LIO_LIThe leaf length of the selected accessions was strongly correlated with GA levels. Higher GA content in wild rice accessions with longer leaves and GA-induced increase in the leaf length via an increase in cell division confirmed a GA-mediated regulation of division zone in rice. Downstream to GA, OsGRF7 and OsGRF8 function for controlling cell division to determine the rice leaf length.
C_LIO_LISpatial control of cell division to determine the division zone size mediated by GA and downstream OsGRF7 and OsGRF8 explains the leaf length differences between the cultivated and wild rice. This mechanism to control rice leaf length might have contributed to optimizing leaf size during domestication.
C_LI Using machine learning to design adeno-associated virus capsids with high likelihood of viral assembly We study the application of machine learning in designing adeno-associated virus (AAV) capsid sequences with high likelihood of viral assembly, i.e. capsid viability. Specifically, we design and implement Origami, a model-based optimization algorithm, to identify highly viable capsid sequences within the vast space of 2033 possibilities. Our evaluation shows that Origami performs well in terms of optimality and diversity of model-designed sequences. Moreover, these sequences are ranked according to their viability score. This helps designing experiments given budget constraint.