Spontaneous emergence of music detectors in a deep neural network Music exists in almost every society, has universal acoustic features, and is processed by distinct neural circuits in humans even with no experience of musical training. These characteristics suggest an innateness of the sense of music in our brain, but it is unclear how this innateness emerges and what functions it has. Here, using an artificial deep neural network that models the auditory information processing of the brain, we show that units tuned to music can spontaneously emerge by learning natural sound detection, even without learning music. By simulating the responses of network units to 35,487 natural sounds in 527 categories, we found that various subclasses of music are strongly clustered in the embedding space, and that this clustering arises from the music-selective response of the network units. The music-selective units encoded the temporal structure of music in multiple timescales, following the population-level response characteristics observed in the brain. We confirmed that the process of generalization is critical for the emergence of music-selectivity and that music-selectivity can work as a functional basis for the generalization of natural sound, thereby elucidating its origin. These findings suggest that our sense of music can be innate, universally shaped by evolutionary adaptation to process natural sound.

One-sentence summaryMusic-selectivity can arise spontaneously in deep neural networks trained for natural sound detection without learning music.
Plasticity of the dopaminergic phenotype and of locomotion in larval zebrafish induced by changes in brain excitability during the embryonic period During the embryonic period, neuronal communication starts before the establishment of the synapses with forms of neuronal excitability, called here Embryonic Neuronal Excitability (ENE). ENE has been shown to modulate the correct unfolding of development transcriptional programs but the global consequences for the developing organisms are not all understood. Here we monitored calcium transients in zebrafish embryos as a proxy for ENE to assess the efficacy of transient pharmacological treatments able to either increase or decrease ENE. Increasing or decreasing ENE for 24 hour at 2 days post fertilization (dpf) promoted respectively an increase or decrease in the post-mitotic differentiation of the dopamine (DA) neurons in the telencephalon and in the olfactory bulb of zebrafish larvae at 6 dpf. This plasticity of dopaminergic specification occurs within a stable population of vMAT2 immuno-reactive cells, hence identifying an unanticipated biological marker for this pool of reserve cells, that can be recruited through ENE.

Modulating ENE also affected locomotion several days after the end of the treatments. In particular, the increase of ENE from 2 to 3 dpf promoted an hyperlocomotion in 6 dpf zebrafish larvae, reminiscent of endophenotypes reported for Attention Deficit with Hyperactivity Disorders and schizophrenia in zebrafish. These results provide a convenient framework to identify environmental factors that could disturb ENE as well as to study the molecular mechanisms linking ENE to the neurotransmitters specification, with clinical relevance for the pathogenesis of neurodevelopmental disorders.

Significance StatementO_LISpontaneous calcium spikes, used as a proxy for Embryonic Neuronal Excitability (ENE), are detected in the forebrain of embryonic zebrafish.
C_LIO_LITransients pharmacological treatments applied by balneation could be used to increase or decrease ENE.
C_LIO_LIThe post-mitotic differentiation of the dopaminergic phenotype is modulated by ENE in the zebrafish forebrain.
C_LIO_LIThe plasticity of the dopaminergic specification occurs within a reserve pool of vMAT2 immuno-reactive cells.
C_LIO_LITransient increase of ENE at the end of the embryonic period induces a hyperlocomotion, a phenotype associated with ADHD and schizophrenia in this model.
C_LIO_LIOur results open clinically relevant perspectives to study the pathogenesis of neurodevelopmental disorders in zebrafish.
C_LI
G2 stem cells orchestrate time-directed, long-range coordination of calcium signaling during skin epidermal regeneration Skin epidermal homeostasis is maintained via constant regeneration by stem cells, which must communicate to balance their self-renewal and differentiation. A key molecular pathway, Ca2+ signaling has been implicated as a signal integrator in developing and wounded epithelial tissues[1, 2, 3, 4]. Yet how stem cells carry out this signaling across a regenerative tissue remains unknown due to significant challenges in studying signaling dynamics in live mice, limiting our understanding of the mechanisms of stem cell communication during homeostasis. To interpret high dimensional signals that have complex spatial and temporal patterns, we combined optimized imaging of Ca2+ signaling in thousands of epidermal stem cells in living mice with a new machine learning tool, Geometric Scattering Trajectory Homology (GSTH). Using a combination of signal processing, data geometry, and topology, GSTH captures patterns of signaling at multiple scales, either between direct or distant stem cell neighbors. Here we show that epidermal stem cells display dynamic intercellular Ca2+ signaling among neighborhoods of up to 10 cells that is surprisingly coordinated and directed through time across a pool of thousands of stem cells. We find that this collective coordination is an emergent property of the stem cell compartment, distinct from excitatory quiescent neuronal tissues. We demonstrate that cycling stem cells, specifically G2 cells, govern homeostatic patterns of Ca2+ signaling. Stem cells in different cell cycle stages dynamically regulate localization of the gap junction component Connexin43 (Cx43). Lastly, we uncouple global from local communication and identify Cx43 as the molecular mediator necessary for connectivity between local signaling neighborhoods. This work provides resolution in how stem cells at different stages of the cell cycle communicate and how that diversity of phases is essential for tissue wide communication and signaling flow during epidermal regeneration. Our approach provides a framework to investigate stem cell populations and their signaling dynamics, previously not possible. Molecular diagnosis of new isolate of tomato yellow leaf curl virus (TYLCV) in Iraq Tomato yield and quality in Iraq have been threatened by a variable range of infections caused by tomato yellow leaf curl virus. In previous studies, the TYLCV isolates were partially characterized using molecular tests for small fragments not the entire length of the virus. Sample of TYLCV-infected tomato has applied in this study to diagnose complete sequence of TYLCV isolate. Three sets of primers that belong to three well-identified strains in Iraq were used in a PCR technique and interestingly the results were negative. A new Iraqi isolate has been characterized as a first novel Iraqi isolate detected ever using next generation (NGS) and bioinformatics techniques. The NGS platform has produced about 78,232,062 paired reads of the TYLCV-infected tomato var. Oula F1. The complete raw reads of the infected variety have been analyzed using RepeatExplorer pipeline and Map to reference. The full sequence of TYLCV was reconstructed and extracted to consist of 2770 nt and then deposited in Genbank under accession number MT583814. Copy numbers and genome proportion of this sequence have been calculated that were 3523 and 0,086% respectively. Phylogenetic analyses of full nucleotide sequences confirmed close relationship to Iranian isolate (TYLCV-Kahnooj) than other published viruses. Additionally, a and {beta} DNA satellites have not discovered in the TYLCV-infected sample. Universality of evolutionary trajectories under arbitrary competition dynamics The assumption of constant population size is central in population genetics. It led to a large body of results, that are robust to modeling choices and that have proven successful to understand evolutionary dynamics. In reality, allele frequencies and population size are both determined by the interaction between a population and the environment. Relaxing the constant-population assumption have two big drawbacks. It increases the technical difficulty of the analysis, and it requires specifying a mechanism for the saturation of the population size, possibly making the results contingent on model details. Here, we develop a framework that encompasses a great variety of systems with an arbitrary mechanism for population growth limitation. By using techniques based on scale separation for stochastic processes, we are able to calculate analytically properties of evolutionary trajectories, such as the fixation probability. Remarkably, these properties assume a universal form with respect to our framework, which depends on only three parameters related to the inter-generation timescale, the invasion fitness, and the carrying capacity of the strains. In other words, different systems, such as Lotka-Volterra or a chemostat model (contained in our framework), share the same evolutionary outcomes after a proper re-mapping of their parameters. An important and surprising consequence of our results is that the direction of selection can be inverted, with a population evolving to reach lower values of invasion fitness. Anaplerotic flux into the Calvin-Benson cycle. Hydrogen isotope evidence for in vivo occurrence in C3 metabolism - As the central carbon uptake pathway in photosynthetic cells, the Calvin-Benson cycle is among the most important biochemical cycles for life on Earth. A carbon flux of anaplerotic origin (i.e., through the chloroplast-localised oxidative branch of the pentose phosphate pathway) into the Calvin-Benson cycle was proposed recently.
- Here, we measured intramolecular deuterium abundances in leaf starch of Helianthus annuus grown at varying ambient CO2 concentrations, Ca. Additionally, we modelled deuterium fractionations expected for the anaplerotic pathway and compared modelled with measured fractionations.
- We report deuterium fractionation signals at H1 and H2 of starch glucose. Below a Ca change point, these signals increase with decreasing Ca consistent with modelled fractionations by anaplerotic flux. Under standard conditions (Ca=450 ppm corresponding to intercellular CO2 concentrations, Ci, of 328 ppm), we estimate negligible anaplerotic flux. At Ca=180 ppm (Ci=140 ppm), more than 10% of the glucose 6-phosphate entering the starch biosynthesis pathway is diverted into the anaplerotic pathway.
- In conclusion, we report evidence consistent with anaplerotic carbon flux into the Calvin-Benson cycle in vivo. We propose the flux may help to (i) maintain high levels of ribulose 1,5-bisphosphate under source-limited growth conditions to facilitate photorespiratory nitrogen assimilation required to build-up source strength and (ii) counteract oxidative stress. Beneficial effects of novel strains of Aureobasidium pullulans produced 1,3-1,6 β-glucans on non-esterified fatty acid levels in diabetic KKAy mice Obesity, metabolic syndrome, associated lipotoxicity and its cascade of events contribute to the majority of the burden related to non-communicable diseases globally. Preventive lifestyle changes aside, several beneficial effects have been reported in type II diabetes mellitus and dyslipidaemia patients with biological response modifier glucans (BRMG) produced as an exopolysaccharide by Aureobasidium pullulans. In this study, we compared two strains (AFO-202 and N-163) that produce beta glucans in alleviating lipotoxicity. This study was performed in obese diabetic mice model of KK-Ay mice, in four groups with six subjects in each group - Group 1: sacrificed on Day 0 for baseline values; Group 2: control (drinking water); Group 3: AFO-202 beta glucan--200 mg/kg/day; Group 4: N-163 beta glucan--300 mg/kg/day. The animals in groups 2-4 had the test solutions administered by gavage once daily for 28 consecutive days. Biochemical analyses were conducted of blood glucose, triglycerides, total cholesterol, LDL cholesterol, HDL cholesterol and non-esterified fatty acids (NEFA). Group 4 (N-163) had the lowest NEFA levels, as compared to the other groups, and marginally decreased triglyceride levels. The groups had no significant differences in blood glucose, HbA1c, triglycerides, or LDL and HDL cholesterol. N-163 produced by A. pullulans decreased NEFA in a diabetic mice model in 28 days. These results, although modest, warrant further in-depth research into lipotoxicity and associated inflammatory cascades in both healthy and disease affected subjects to develop novel strategies for prevention and management. Loss of Nuclear DNA Ligase III Reverts PARP Inhibitor Resistance in BRCA1/53BP1 Double-deficient Cells by Exposing ssDNA Gaps Inhibitors of poly(ADP-ribose) (PAR) polymerase (PARPi) have entered the clinic for the treatment of homologous recombination (HR)-deficient cancers. Despite the success of this approach, preclinical and clinical research with PARPi has revealed multiple resistance mechanisms, highlighting the need for identification of novel functional biomarkers and combination treatment strategies. Functional genetic screens performed in cells and organoids that acquired resistance to PARPi by loss of 53BP1 identified loss of LIG3 as an enhancer of PARPi toxicity in BRCA1-deficient cells. Enhancement of PARPi toxicity by LIG3 depletion is dependent on BRCA1 deficiency but independent of the loss of 53BP1 pathway. Mechanistically, we show that LIG3 loss promotes formation of MRE11-mediated post-replicative ssDNA gaps in BRCA1-deficient and BRCA1/53BP1 double-deficient cells exposed to PARPi, leading to an accumulation of chromosomal abnormalities. LIG3 depletion also enhances efficacy of PARPi against BRCA1-deficient mammary tumors in mice, suggesting LIG3 as a potential therapeutic target. Unevolved proteins from modern and prebiotic amino acids manifest distinct structural profiles Natural proteins represent numerous but tiny structure/function islands in a vast ocean of possible protein sequences, most of which has not been explored by either biological evolution or research. Recent studies have suggested this uncharted sequence space possesses surprisingly high structural propensity, but development of an understanding of this phenomenon has been awaiting a systematic high-throughput approach.

Here, we designed, prepared, and characterized two combinatorial protein libraries consisting of randomized proteins, each 105 residues in length. The first library constructed proteins from the entire canonical alphabet of 20 amino acids. The second library used a subset of only 10 residues (A,S,D,G,L,I,P,T,E,V) that represent a consensus view of plausibly available amino acids through prebiotic chemistry. Our study shows that compact conformations resistant to proteolysis are (i) abundant (up to 40%) in random sequence space, (ii) independent of general Hsp70 chaperone system activity, and (iii) not granted solely by "late" and complex amino acid additions. The Hsp70 chaperone system effectively increases solubility and refoldability of the canonical alphabet but has only a minor impact on the "early" library. The early alphabet proteins are inherently more soluble and refoldable, possibly assisted by the cell-like environment in which these assays were performed.

Our work indicates that both early and modern amino acids are predisposed to supporting protein structure (either in forms of oligomers or globular/molten globule structures) and that protein structure may not be a unique outcome of evolution. Multiomic analisys reveals that viroid infection induces a temporal reprograming of plant-defence mechanisms at multiple regulatory levels Viroids are circular RNAs of minimal complexity compelled to subvert plant-regulatory networks to accomplish their infectious process. Studies focused on the response to viroid infection have mostly addressed specific regulatory levels and considered a unique infection time. Thus, much remains to be done to understand the temporal evolution and complex nature of viroid-host interactions. Here we present an integrative analysis of the temporal evolution and intensity of the genome-wide alterations in cucumber plants infected with hop stunt viroid (HSVd) by integrating differential host transcriptome, sRNAnome and methylome. Our results support that HSVd promotes the redesign of the cucumber regulatory-pathways predominantly affecting specific regulatory layers at different infection-phases. The initial response was characterized by a reconfiguration of the host-transcriptome by differential exon usage, followed by a progressive transcriptional down-regulation modulated by epigenetic changes. Regarding endogenous small RNAs, the alterations were limited and mainly occur at the late stage. The most significant host-alterations were predominantly related to the down-regulation of transcripts involved in plant-defence mechanisms, the restriction of pathogen-movement and the systemic spreading of defence signals. Altogether our data evidence the existence of a dynamic and yet poorly known arms race between the host and the viroid. We expect that these data constituting the first comprehensive map of the plant responses to a viroid infection contribute to elucidate the molecular basis of this multifaceted defence and counter-defence layout. Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures PurposeCombinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning based signatures (with 8 to 20% misclassification rates). These signatures can quantify therapeutically-relevant as well as accidental radiation exposures. The prodromal symptoms of Acute Radiation Syndrome (ARS) overlap those present in Influenza and Dengue Fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

MethodsThis study investigated recall by previous and novel radiation signatures independently derived from multiple Gene Expression Omnibus datasets on common and rare non-malignant blood disorders and blood-borne infections (thromboembolism, S. aureus bacteremia, malaria, sickle cell disease, polycythemia vera, and aplastic anemia). Normalized expression levels of signature genes are used as input to machine learning-based classifiers to predict radiation exposure in other hematological conditions.

ResultsExcept for aplastic anemia, these blood-borne disorders modify the normal baseline expression values of genes present in radiation signatures, leading to false-positive misclassification of radiation exposures in 8 to 54% of individuals. Shared changes, predominantly in DNA damage response and apoptosis-related gene transcripts in radiation and confounding hematological conditions, compromise the utility of these signatures for radiation assessment. These confounding conditions (sickle cell disease, thromboembolism, S. aureus bacteremia, malaria) induce neutrophil extracellular traps, initiated by chromatin decondensation, DNA damage response and fragmentation followed by programmed cell death. Riboviral infections (for example, Influenza or Dengue fever) have been proposed to bind and deplete host RNA binding proteins, inducing R-loops in chromatin. R-loops that collide with incoming replication forks can result in incompletely repaired DNA damage, inducing apoptosis and releasing mature virus. To mitigate the effects of confounders, we evaluated predicted radiation-positive samples with novel gene expression signatures derived from radiation-responsive transcripts encoding secreted blood plasma proteins whose expression levels are unperturbed by these conditions.

ConclusionsThis approach identifies and eliminates misclassified samples with underlying hematological or infectious conditions, leaving only samples with true radiation exposures. Diagnostic accuracy is significantly improved by selecting genes that maximize both sensitivity and specificity in the appropriate tissue using combinations of the best signatures for each of these classes of signatures. Highly efficient synthetic CRISPR RNA/Cas9-based mutagenesis for rapid cardiovascular phenotypic screening in F0 zebrafish The zebrafish is a valuable vertebrate model to study cardiovascular formation and function due to the facile visualization and rapid development of the circulatory system in its externally growing embryos. Despite having distinct advantages, zebrafish have paralogs of many important genes, making reverse genetics approaches inefficient since generating animals bearing multiple gene mutations requires substantial efforts. Here, we present a simple and robust synthetic CRISPR RNA/Cas9-based mutagenesis approach for generating biallelic F0 zebrafish knockouts. Using a dual-guide synthetic CRISPR RNA/Cas9 ribonucleoprotein (dgRNP) system, we compared the efficiency of biallelic gene disruptions following the injections of one, two, and three dgRNPs per gene into the cytoplasm or yolk. We show that simultaneous cytoplasmic injections of three distinct dgRNPs per gene into one-cell stage embryos resulted in the most efficient and consistent biallelic gene disruptions. Importantly, this triple dgRNP approach enables efficient inactivation of cell autonomous and cell non-autonomous gene function, likely due to the low mosaicism of biallelic disruptions. In support of this finding, we provide evidence that the F0 animals generated by this method fully phenocopied the endothelial and peri-vascular defects observed in corresponding stable mutant homozygotes. Moreover, this approach faithfully recapitulated the trunk vessel phenotypes resulting from the genetic interaction between two vegfr2 zebrafish paralogs. Mechanistically, investigation of genome editing and mRNA decay indicates that the combined mutagenic actions of three dgRNPs per gene lead to an increased probability of frameshift mutations, enabling efficient biallelic gene disruptions. Therefore, our approach offers a highly robust genetic platform to quickly assess novel and redundant gene function in F0 zebrafish. Climate warming changes synchrony of plants and pollinators Climate warming changes the phenology of many species. When interacting organisms respond differently, climate change may disrupt their interactions and affect the stability of ecosystems. Here, we used GBIF occurrence records to examine phenology trends in plants and their associated insect pollinators in Germany since the 1980s. We found strong phenological advances in plants, but differences in the extent of shifts among pollinator groups. The temporal trends in plant and insect phenologies were generally associated with interannual temperature variation, and thus likely driven by climate change. When examining the synchrony of species-level plant-pollinator interactions, their temporal trends differed among pollinator groups. Overall, plant-pollinator interactions become more synchronized, mainly since the phenology of plants responded more strongly to climate change than that of the pollinators. However, if the observed trends continue, many interactions may become more asynchronous again in the future. Our study suggests that climate change affects the phenologies of both plants and insects, and that it also influences the synchrony of plant-pollinator interactions. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Changes in Behavior and Salivary Serum Amyloid A in cows with Subclinical Mastitis The aim of this study was to identify detailed changes in behavior, and in salivary serum amyloid A (SAA), associated with subclinical mastitis. This included standard sickness behaviors (which form part of an adaptive response to conserve energy, minimize heat loss and facilitate recovery following infection and inflammation) and lesser-studied behaviors, that are biologically predicted to change at low-level infection, and therefore particularly relevant for detecting subclinical mastitis (here labelled  luxury behaviors). SAA is a physiological marker of systemic inflammation, with levels in milk and serum already known to increase during subclinical mastitis. We investigated whether the same was true for SAA in cow saliva. Data were collected for n = 34 commercial barn-housed dairy cows, tested in 17 matched-pairs. Each pair comprised a cow with subclinical mastitis (SCM) and a healthy control (CTRL), identified using somatic cell count (SCC) (SCM: SCC >200 x1000 cells/ml; CTRL: SCC <100 x1000 cells/ml). SCM cows were selected for study ad-hoc, at which point they were paired with a CTRL cow, based upon parity and calving date; consequently, the full data set was accrued over several months. Data were collected for each pair over 3 days: SCC (l4:00-l5:00h) Day 1; behavior (24h from 00:00h) Day 2; salivary serum amyloid-A (SAA) Day 3. We report, for the first time, that an increase in salivary SAA occurs during subclinical mastitis; SAA was higher in SCM cows and demonstrated a positive (weak) correlation with SCC. The behavioral comparisons revealed that SCM cows had reductions in activity (behavioral transitions and distance moved), social exploration, social reactivity (here: likelihood to move away/be displaced following receipt of agonism), performance of social grooming and head butts, and the receipt of agonistic non-contact challenges. In addition, SCM cows received more head swipes, and spent a greater proportion of time lying with their head on their flank than CTRL cows. SCM cows also displayed an altered feeding pattern; they spent a greater proportion of feeding time in direct contact with two conspecifics, and a lower proportion of feeding time at self-locking feed barriers, than CTRL cows. Behavioral measures were found to correlate, albeit loosely, with serum SAA in a direction consistent with predictions for sickness behavior. These included positive correlations with both lying duration and the receipt of all agonistic behavior, and negative correlations with feeding, drinking, the performance of all social and all agonistic behavior, and social reactivity. We conclude that changes in salivary SAA, social behavior, and activity offer potential in the detection of subclinical mastitis and recommend further investigation to substantiate and refine our findings. 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. RNA splicing analysis using heterogeneous and large RNA-seq datasets The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity. We describe here a suite of algorithms and tools implemented in the MAJIQ v2 package to address challenges in detection, quantification, and visualization of splicing variations from such datasets. Using both large scale synthetic data and GTEx v8 as benchmark datasets, we demonstrate that the approaches in MAJIQ v2 outperform existing methods. We then apply MAJIQ v2 package to analyze differential splicing across 2,335 samples from 13 brain subregions, demonstrating its ability to offer new insights into brain subregion-specific splicing regulation. Small extracellular vesicles from young mice prevent frailty, improve healthspan and decrease epigenetic age in old mice. Aging is associated with an increased risk of frailty, disability, comorbidities, institutionalization, falls, fractures, hospitalization, and mortality. Searching for strategies to delay the degenerative changes associated with aging and frailty is interesting. We treated old animals intravenously with small extracellular vesicles (sEVs) derived from adipose mesenchymal stem cells (ADSCs) of young animals, and we found an improvement of several functional parameters usually altered with aging, such as motor coordination, grip strength, fatigue resistance, fur regeneration, and renal function. Frailty index analysis showed that 40% of old control mice were frail, whereas none of the old ADSCs-sEVs treated mice were. Molecular and structural benefits in muscle and kidney accompanied this functional improvement. ADSCs-sEVs induced pro-regenerative effects and a decrease in oxidative stress, inflammation, and senescence markers. Moreover, predicted epigenetic age was lower in tissues of old mice treated with ADSCs-sEVs and their metabolome changed to a youth-like pattern. Finally, we gained some insight into the miRNAs contained in sEVs that might be, at least in part, responsible for the effects observed. We propose that young sEVs treatment can be beneficial against frailty and therefore can promote healthy aging. Glucose inhibits haemostasis and accelerates diet-induced hyperlipidaemia in zebrafish larvae Hyperglycaemia damages the microvasculature in part through the reduced recruitment of immune cells and interference with platelet signalling, leading to poor wound healing and accelerated lipid deposition in mammals. We investigated the utility of zebrafish larvae to model the effect of glucose on neutrophil and macrophage recruitment to a tail wound, wound-induced haemostasis, and chicken egg yolk feed challenge-induced hyperlipidaemia by supplementing larvae with exogenous glucose by immersion or injection. Neither method of glucose supplementation affected the recruitment of neutrophils and macrophages following tail transection. Glucose injection reduced thrombocyte retention and fibrin plug formation while only thrombocyte retention was reduced by glucose immersion following tail transection. We observed accelerated lipid accumulation in glucose-injected larvae challenged with high fat chicken egg yolk feeding. Our study identifies conserved and divergent effects of high glucose on inflammation, haemostasis, and hyperlipidaemia in zebrafish larvae compared to mammals. Systems analysis shows a role of cytophilic antibodies in shaping innate tolerance to malaria The mechanism of acquisition and maintenance of natural immunity against Plasmodium falciparum malaria remains unclear. Although, clinical immunity develops over time with repeated malaria episodes, disease tolerance is more rapidly acquired compared to protective immunity. It remains unclear, how pre-existing immune responses impacts the mechanism responsible for disease tolerance. Here, we investigated a cohort of returning travelers treated for acute symptomatic P. falciparum malaria, either infected for the first time, or with a previous history of malaria. Through repeated sampling over one year in a malaria free setting, we were able to study the acute and longitudinal effects of the infection. We combined comprehensive immune cell and plasma protein profiling with integrated and data driven analysis, describing the immune landscape from acute disease to one year after infection. We identified a strong association between pro-inflammatory signatures and {gamma}{delta} T cell expansion. The association was significantly impacted by previous exposure to malaria, resulting in a dampened pro-inflammatory response, which translated to reduced V{delta}2+ {gamma}{delta} T cell expansion compared to primary infected individuals. The dampened inflammatory signal was associated with early expansion of Fc{gamma}RIII+ monocytes and parasite-specific antibodies of IgG1 and IgG3 isotypes.

Our data suggest that the interplay of Fc{gamma}RIII+ monocytes and a cytophilic parasite-specific IgG during the early blood stage infection lead to lower parasitemia and a dampened pro-inflammatory response with reduced {gamma}{delta} T cell expansion. This enhanced control and reduced inflammation points to a potential mechanism on how tolerance is established following repeated malaria exposure.

One Sentence SummaryA systems immunology analysis on natural malaria sheds light on disease tolerance mechanism associated with gamma delta T cell expansion Hierarchical clustering optimizes the tradeoff between compositionality and expressivity of task structures for flexible reinforcement learning A hallmark of human intelligence, but challenging for reinforcement learning (RL) agents, is the ability to compositionally generalise, that is, to recompose familiar knowledge components in novel ways to solve new problems. For instance, when navigating in a city, one needs to know the location of the destination and how to operate a vehicle to get there, whether it be pedalling a bike or operating a car. In RL, these correspond to the reward function and transition function, respectively. To compositionally generalize, these two components need to be transferable independently of each other: multiple modes of transport can reach the same goal, and any given mode can be used to reach multiple destinations. Yet there are also instances where it can be helpful to learn and transfer entire structures, jointly representing goals and transitions, particularly whenever these recur in natural tasks (e.g., given a suggestion to get ice cream, one might prefer to bike, even in new towns). Prior theoretical work has explored how, in model-based RL, agents can learn and generalize task components (transition and reward functions). But a satisfactory account for how a single agent can simultaneously satisfy the two competing demands is still lacking. Here, we propose a hierarchical RL agent that learns and transfers individual task components as well as entire structures (particular compositions of components) by inferring both through a non-parametric Bayesian model of the task. It maintains a factorised representation of task components through a hierarchical Dirichlet process, but it also represents different possible covariances between these components through a standard Dirichlet process. We validate our approach on a variety of navigation tasks covering a wide range of statistical correlations between task components and show that it can also improve generalisation and transfer in more complex, hierarchical tasks with goal/subgoal structures. Finally, we end with a discussion of our work including how this clustering algorithm could conceivably be implemented by cortico-striatal gating circuits in the brain. Comparing genome-based estimates of relatedness for use in pedigree-based conservation management Researchers have long debated which estimator of relatedness best captures the degree of relationship between two individuals. In the genomics era, this debate continues, with relatedness estimates being sensitive to the methods used to generate markers, marker quality, and levels of diversity in sampled individuals. Here, we compare six commonly used genome-based relatedness estimators (kinship genetic distance (KGD), Wang Maximum Likelihood (TrioML), Queller and Goodnight (Rxy), Kinship INference for Genome-wide association studies (KING-robust), and Pairwise Relatedness (RAB), allele-sharing co-ancestry (AS)) across five species bred in captivity-including three birds and two mammals-with varying degrees of reliable pedigree data, using reduced-representation and whole genome resequencing data. Genome-based relatedness estimates varied widely across estimators, sequencing methods, and species, yet the most consistent results for known first order relationships were found using Rxy, RAB, and AS. However, AS was found to be less consistently correlated with known pedigree relatedness than either Rxy or RAB. Our combined results indicate there is not a single genome-based estimator that is ideal across different species and data types. To determine the most appropriate genome-based relatedness estimator for each new dataset, we recommend assessing the relative: (1) correlation of candidate estimators with known relationships in the pedigree and (2) precision of candidate estimators with known first-order relationships. These recommendations are broadly applicable to conservation breeding programs, particularly where genome-based estimates of relatedness can complement and complete poorly pedigreed populations. Given a growing interest in the application of wild pedigrees, our results and are also applicable to in-situ wildlife management. Genomically Mined Acoustic Reporter Genes Enable In Vivo Monitoring of Tumors and Tumor-Homing Bacteria A major outstanding challenge in the fields of biological research, synthetic biology and cell-based medicine is the difficulty of visualizing the function of natural and engineered cells noninvasively inside opaque organisms. Ultrasound imaging has the potential to address this challenge as a widely available technique with a tissue penetration of several centimeters and spatial resolution below 100 {micro}m. Recently, the first genetically encoded acoustic reporters were developed based on bacterial gas vesicles to link ultrasound signals to molecular and cellular function. However, the properties of these first-generation acoustic reporter genes (ARGs) resulted in limited sensitivity and specificity for imaging in the in vivo context. Here, we describe second-generation ARGs with greatly improved acoustic properties and expression characteristics, identified through a phylogenetic screen of candidate gene clusters from diverse bacteria and archaea. The resulting constructs offer major qualitative and quantitative improvements, including much stronger ultrasound contrast, the ability to produce nonlinear signals distinguishable from background tissue, and stable long-term expression. We demonstrate the utility of these next-generation ARGs by imaging in situ gene expression in mouse models of breast cancer and tumor-homing probiotic bacteria, revealing the unique spatial distributions of tumor growth and colonization by therapeutic cells noninvasively in living subjects. Visualization of bacterial type 3 secretion system components down to the molecular level by MINFLUX nanoscopy Type 3 secretion systems (T3SS) are essential virulence factors of numerous bacterial pathogens and inject effector proteins into host cells. The needle-like T3SS machinery consists of more than 20 components, has a length of around 100 nm and a diameter of up to 30 nm according to EM studies. Its intrabacterial components are highly dynamic and in permanent exchange with other bacterial structures. Therefore, a temporally and spatially resolved visualization of the T3SS using fluorescence microscopy techniques has been challenging. In the present study, novel labeling strategies were combined with super-resolution microscopy such as STED, STORM and MINFLUX. MINFLUX nanoscopy allowed to visualize components of the T3SS machinery such as the dynamic sorting platform component YscL and the extrabacterial pore protein YopD at unprecedented resolutions. The presented results represent the basis for an in depth investigation of T3SS structure and function and therefore gain new insights into the infection process of human pathogens in order to develop novel treatment and prevention strategies. Birth Order Differences in Education Originate in Post-Natal Environments Siblings share many environments and much of their genetics. Yet, siblings turn out different. Intelligence and education are influenced by birth order, with earlier-born siblings outperforming later-borns. We investigate whether birth order differences in education are caused by biological differences present at birth, that is, genetic differences or in-utero differences. Using family data that spans two generations, combining registry, survey, and genotype information, this study is based on the Norwegian Mother, Father and Child Cohort Study (MoBa). We show that there are no genetic differences by birth order as captured by polygenic scores (PGSs) for educational attainment. Furthermore, we show that earlier-born have lower birth weight than later-born, indicating worse uterine environments. Educational outcomes are still higher for earlier-born children when we adjust for PGSs and in utero variables, indicating that birth order differences arise post-natally. Finally, we consider potential environmental influences, such as differences according to maternal age, parental educational attainment, and sibling genetic nurture. We show that birth order differences are not biological in origin, but pinning down their specific causes remains elusive. Hidden dynamics of proteasome autoregulation discovered by cryo-EM data-driven deep learning The cellular functions are executed by macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving conformational continuum of important complexes at atomic level remains a key challenge in the methodology of computational biophysics. Here we introduce a deep-learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy reconstructions of nonequilibrium conformational continuum. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. Applications of this methodology to six experimental datasets demonstrated its generality in breaking resolution barrier of visualizing dynamic components of functional complexes, in choreographing continuous inter-subunit motions and in exploring their  hidden conformational space. Importantly, AlphaCryo4D identified 64 conformers of the substrate-bound human 26S proteasome and reconstituted single-nucleotide-exchange dynamics of proteasomal AAA-ATPase motor during translocation initiation, which together illuminates a grand hierarchical allostery for proteasome autoregulation.