Distributions of extinction times from fossil ages and tree topologies: the example of mid-Permian synapsid extinctions Given a phylogenetic tree that includes only extinct, or a mix of extinct and extant taxa, where at least some fossil data are available, we present a method to compute the distribution of the extinction time of a given set of taxa under the Fossilized-Birth-Death model.

Our approach differs from the previous ones in that it takes into account (i) the possibility that the taxa or the clade considered may diversify before going extinct and (ii) the whole phylogenetic tree to estimate extinction times, whilst previous methods do not consider the diversification process and deal with each branch independently. Because of this, our method can estimate extinction times of lineages represented by a single fossil, provided that they belong to a clade that includes other fossil occurrences.

We assess and compare our new approach with a standard previous one using simulated data. Results show that our method provides more accurate confidence intervals.

This new approach is applied to the study of the extinction time of three Permo-Carboniferous synapsid taxa (Ophiacodontidae, Edaphosauridae, and Sphenacodontidae) that are thought to have disappeared toward the end of the Cisuralian (early Permian), or possibly shortly thereafter. The timing of extinctions of these three taxa and of their component lineages supports the idea that the biological crisis in the late Kungurian/early Roadian consisted of a progressive decline in biodiversity throughout the Kungurian.
On the incongruence of genotype-phenotype and fitness landscapes The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, yet it changes reciprocal sign epistasis into simple sign epistasis and no sign epistasis with equal probability. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.

AUTHOR SUMMARYHow do mutations change phenotypic traits and organismal fitness? This question is often addressed in the context of a classic metaphor of evolutionary theory -- the fitness landscape. A fitness landscape is akin to a physical landscape, in which genotypes define spatial coordinates, and fitness defines the elevation of each coordinate. Evolution then acts like a hill-climbing process, in which populations ascend fitness peaks as a consequence of mutation and selection. It is becoming increasingly common to construct such landscapes using experimental data from high-throughput sequencing technologies and phenotypic assays, in systems such as macromolecules and gene regulatory circuits. Although these landscapes are typically defined by molecular phenotypes, and are therefore more appropriately referred to as genotype-phenotype landscapes, they are often used to study evolutionary dynamics. This requires the assumption that the molecular phenotype is a reasonable proxy for fitness, which need not be the case. For example, selection may favor a low or intermediate phenotypic value, causing incongruence between a fitness landscape and its underlying genotype-phenotype landscape. Here, we study such incongruence using a diversity of theoretical models and experimental data from gene regulatory systems. We regularly find incongruence, in that fitness landscapes tend to comprise more peaks than their underlying genotype-phenotype landscapes. However, using evolutionary simulations, we show that this increased ruggedness need not impede adaptation.
A network approach to genetic circuit designs As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information. A General Biphasic-Bodyweight Model for Scaling Basal Metabolic Rate, Glomerular Filtration Rate and Drug Clearance from Birth to Adulthood Understanding the maturation process of human physiology and metabolism has broad medical and pharmaceutical implications. Age and bodyweight are frequently considered as separate variables in modeling the dynamical changes of human organ functions and of drug clearance from birth to adulthood. The objective of this study is to propose a unified, continuous and bodyweight-only equation to quantify the changes of human basal metabolic rate (BMR), glomerular filtration rate (GFR) and drug clearance (CL) from infancy to adulthood. The BMR datasets were retrieved from a comprehensive historical database of male and female subjects (0.02 to 64 years). The CL datasets for 17 drugs and the GFR dataset were generated from age-incorporated maturation-and-growth models with reported parameter values. The model used in the simulation is independent of the proposed model. A statistical approach was used to simulate the model generated CL and GFR data for a hypothetical population with 26 age groups (ranging from 0 to 20 years). Besides, individual CL data for one drug, and sparse PBPK-modeled CL values for two drugs were also included for analysis. A 4-parameter, mixed-allometry equation with two power-law functions of bodyweight was proposed and evaluated as a general model using nonlinear regression and dimensionless analysis. All datasets universally reveal biphasic curves with two distinct linear segments on log-log plots. Compared with simple allometry, the biphasic model fits satisfactorily to all datasets (based on Akaikes Information Criterion and residual plots). The biphasic equation consists of two reciprocal allometric terms that asymptotically determine the overall curvature. The fitting results show a superlinear scaling phase (slope >1; ca. 1.5 - 3.5) below the characteristic bodyweight at the phase transition; and above which, a sublinear scaling phase (slope <1; ca. 0.5 - 0.7) is evident. The phase-transition bodyweight is ranging from 5 to 20 kg (corresponding to 0.5 - 9 years) and the mean value is around 10 kg ([~]2 years) for all data sets. The dimensionless analysis generalizes, and offers quantitative realization of, the maturation and growth process. In conclusion, the proposed mixed-allometry equation is a generic model that quantitatively describes the phase transition occurring in the human maturation process of BMR, GFR and drug CL. 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. Insertions in SARS-CoV-2 genome caused by template switch and duplications give rise to new variants that merit monitoring The appearance of multiple new SARS-CoV-2 variants during the winter of 2020-2021 is a matter of grave concern. Some of these new variants, such as B.1.617.2, B.1.1.7, and B.1.351, manifest higher infectivity and virulence than the earlier SARS-CoV-2 variants, with potential dramatic effects on the course of the COVID-19 pandemic. So far, analysis of new SARS-CoV-2 variants focused primarily on point nucleotide substitutions and short deletions that are readily identifiable by comparison to consensus genome sequences. In contrast, insertions have largely escaped the attention of researchers although the furin site insert in the spike protein is thought to be a determinant of SARS-CoV-2 virulence and other inserts might have contributed to coronavirus pathogenicity as well. Here, we investigate insertions in SARS-CoV-2 genomes and identify 347 unique inserts of different lengths. We present evidence that these inserts reflect actual virus variance rather than sequencing errors. Two principal mechanisms appear to account for the inserts in the SARS-CoV-2 genomes, polymerase slippage and template switch that might be associated with the synthesis of subgenomic RNAs. We show that inserts in the Spike glycoprotein can affect its antigenic properties and thus merit monitoring. At least, three inserts in the N-terminal domain of the Spike (ins245IME, ins246DSWG, and ins248SSLT) that were first detected in 2021 are predicted to lead to escape from neutralizing antibodies, whereas other inserts might result in escape from T-cell immunity. Citation needed? Wikipedia and 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. Sarcoplasmic reticulum calcium handling in young DBA/2J vs C57BL/10 mdx models of Duchenne muscular dystrophy The DBA/2J (D2) mdx mouse has emerged as a more severe model of Duchenne muscular dystrophy when compared to the traditional C57BL/10 (C57) mdx mouse. Here, we questioned whether sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) function would differ in muscles from young D2 and C57 mdx mice. In gastrocnemius muscles, both D2- and C57 mdx mice exhibited signs of impaired Ca2+ uptake, however, this was more severe in D2 mdx mice. Maximal SERCA activity was lowered only in D2 mdx gastrocnemius muscles and not C57 mdx muscles. Furthermore, in the left ventricle and diaphragm, Ca2+ uptake was impaired in C57 mdx muscles with lowered rates of Ca2+ uptake compared with C57 WT mice, whereas in muscles from D2 mdx mice, rates of Ca2+ uptake were unattainable due to the severe impairments in their ability to transport Ca2+. Overall, our study demonstrates that SERCA function is drastically impaired in young D2 mdx mice. Flavobacterium johnsoniae Tyrosine Ammonia Lyase (FjTAL) in-silico Structure Prediction and Molecular Docking to L-Tyrosine, p-Coumaric Acid (pHCA) and Caffeic Acid Responsible for the conversion of L-tyrosine to p-coumaric acid in Flavobacterium johnsoniae, FjTAL has drawn the attention of many biochemical engineers who wish to carry out a sustainable biosynthetic scheme for the production of aromatic compounds. In this study, with the aid of various computational tools, the secondary and tertiary structures of FjTAL have been predicted. The results suggest that FjTAL forms a homo-tetramer when active as a cytosolic enzyme and it is mostly consisted of alpha helices. With the aid of molecular docking, one can hypothesize that FjTAL is likely to bind to L-tyrosine, p-coumaric acid, and caffeic acid with a similar molecular mechanism and thus, p-coumaric acid and caffeic acid may exhibit a negative feedback response toward the enzyme and inhibit its activity competitively. Two distinct binding pockets have been discovered, one of which contains highly conserved residues among several species. The residues which form the prosthetic group 3,5-dihydro-5-methylidene-4H-imidazol-4-one (MIO) also emerge in the evolutionary conserved binding pocket. The other discovered cavity, could either be a second binding site for the ligands or simply an artifact of the molecular docking task. Daily torpor reduces the energetic consequences of habitat selection for a widespread bat Homeothermy requires increased metabolic rates as temperatures decline below the thermoneutral zone, so homeotherms typically select microhabitats within or near their thermoneutral zones during periods of inactivity. However, many mammals and birds are heterotherms that relax internal controls on body temperature when maintaining a high, stable body temperature is energetically costly. Such heterotherms should be less tied to microhabitats near their thermoneutral zones, and because heterotherms spend more time in torpor and expend less energy at colder temperatures, heterotherms may even select microhabitats in which temperatures are well below their thermoneutral zones. We studied how temperature and daily torpor influence selection of diurnal roosts by a heterothermic bat (Myotis thysanodes). We (1) quantified the relationship between ambient temperature and daily duration of torpor, (2) simulated daily energy expenditure over a range of microhabitat (roost) temperatures, and (3) quantified the influence of roost temperature on roost selection. While warm roosts substantially reduced energy expenditure of simulated homeothermic bats, heterothermic bats modulated their use of torpor to maintain a constant level of energy expenditure over the course of a day. Daily torpor expanded the range of energetically economical microhabitats, such that roost selection was independent of roost temperature. Our work adds to a growing literature documenting functions of torpor beyond its historical conceptualization as a last-resort measure to save energy during extended or acute energetic stress. A vesicle microrheometer for high-throughput viscosity measurements of lipid and polymer membranes Viscosity is a key property of cell membranes that controls mobility of embedded proteins and membrane remodeling. Measuring it is challenging because existing approaches involve complex experimental designs and/or models, and the applicability of some is limited to specific systems and membrane compositions. As a result there is scarcity of data and the reported values for membrane viscosity vary by orders of magnitude for the same system. Here, we show how viscosity of bilayer membranes can be obtained from the transient deformation of giant unilamellar vesicles. The approach enables a non-invasive, probe-independent and high-throughput measurement of the viscosity of bilayers made of lipids or polymers with a wide range of compositions and phase state. Pure lipid and single-phase mixed bilayers are found to behave as Newtonian fluids with strain-rate independent viscosity, while phase-separated and diblock-copolymers systems exhibit shear-thinning in the explored range of strain rates 1-2000 s-1. The results also reveal that electrically polarized bilayers can be significantly more viscous than charge-neutral bilayers. These findings suggest that biomembrane viscosity is a dynamic property that can be actively modulated not only by composition but also by membrane polarization, e.g., as in action potentials. Large-scale analysis of SARS-CoV-2 synonymous mutations reveals the adaptation to the human codon usage during the virus evolution Many large national and transnational studies have been dedicated to the analysis of SARS-CoV-2 genome, most of which focused on missense and nonsense mutations. However, approximately 30% of the SARS-CoV-2 variants are synonymous, therefore changing the target codon without affecting the corresponding protein sequence.

By performing a large-scale analysis of sequencing data generated from almost 400,000 SARS-CoV-2 samples, we show that silent mutations increasing the similarity of viral codons to the human ones tend to fixate in the viral genome over-time. This indicates that SARS-CoV-2 codon usage is adapting to the human host, likely improving its effectiveness in using the human aminoacyl-tRNA set through the accumulation of deceitfully neutral silent mutations.

One-Sentence SummarySynonymous SARS-CoV-2 mutations related to the activity of different mutational processes may positively impact viral evolution by increasing its adaptation to human codon usage. Dynamic modulation of enhancer responsiveness by core promoter elements in living Drosophila embryo Regulatory interactions between enhancers and core promoters are fundamental for the temporal and spatial specificity of gene expression in development. The central role of core promoters is to initiate productive transcription in response to enhancers activation cues. However, it has not been systematically assessed how individual core promoter elements affect the induction of transcriptional bursting by enhancers. Here, we provide evidence that each core promoter element dynamically alters "enhancer responsiveness" by changing functional parameters of transcriptional bursting in developing Drosophila embryos. Quantitative live imaging analysis revealed that the timing and the continuity of burst induction are common regulatory steps on which core promoter elements impact. We also show that core promoters use the upstream TATA box as an amplifier of transcriptional bursting upon interaction with enhancers. Genome editing analysis of the pair-rule gene fushi tarazu further revealed that the endogenous TATA box and the downstream core promoter element are both essential for the correct expression and the function of key developmental genes in early embryos. We suggest that core promoter elements serve as a key regulatory module in converting enhancer activity into transcription dynamics during animal development. High-throughput variant detection using a color-mixing strategy Many diseases are related to multiple genetic alterations along a single gene. Probing for highly multiple (>10) variants in a single qPCR tube is not possible due to a limited number of fluorescence channels and one variant per channel, so many more tubes are needed. Here, we experimentally validate our novel color-mixing strategy that uses fluorescence combinations as digital color codes to probe multiple variants simultaneously. The color-mixing strategy relies on a simple intra-tube assay that can probe for 15 variants as part of an inter-tube assay that can probe for an exponentially increased number of variants. The color-mixing strategy is achieved using multiplex double-stranded toehold probes modified with fluorophores and quenchers; the probes are designed to be quenched or luminous after binding to wildtype or variant templates. We used the color-mixing strategy to probe for 21 pathogenic mutations in thalassemia and to distinguish between heterozygous and homozygous variants in 6 tubes, with a specificity of 99% and a sensitivity of 94%. To support tuberculosis diagnosis, we used the same strategy to simultaneously probe in Mycobacterium tuberculosis for rifampicin-resistance mutations occurring within one 81-bp region and one 48-bp region in rpoB gene, plus five isoniazid-resistance mutations in inhA and katG genes. Drug screening at single-organoid resolution via bioprinting and interferometry High-throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms for high-throughput screening use two-dimensional cultures of immortalized cell lines which do not accurately reflect the biology of human tumors. More clinically relevant model systems, such as three-dimensional tumor organoids, can be difficult to screen and scale. For example, manually seeded organoids coupled to destructive endpoint assays allow for the characterization of response to treatment, but do not capture the transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We therefore developed a pipeline to generate bioprinted tumor organoids linked to label-free, real-time imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D organoid structures that preserve tumor histology and gene expression. HSLCI imaging in tandem with machine learning-based image segmentation and organoid classification tools enables accurate, label-free parallel mass measurements for thousands of bioprinted organoids. We demonstrate that our method quantitatively identifies individual organoids as insensitive, transiently sensitive, or persistently sensitive to specific treatments. This opens new avenues for rapid, actionable therapeutic selection using automated tumor organoid screening. Autophagosomes fuse to phagosomes and facilitate the degradation of apoptotic cells in Caenorhabditis elegans Autophagosomes are double-membrane intracellular vesicles that degrade protein aggregates, intracellular organelles, and other cellular components. During the development of the nematode Caenorhabditis elegans, many somatic and germ cells undergo apoptosis. These cells are engulfed and degraded by their neighboring cells. We discovered a novel role of autophagosomes in facilitating the degradation of apoptotic cells using a real-time imaging technique. Specifically, the double-membrane autophagosomes in engulfing cells are recruited to the surfaces of phagosomes containing apoptotic cells and subsequently fuse to phagosomes, allowing the inner vesicle to enter the phagosomal lumen. Mutants defective in the production of autophagosomes display significant defects in the degradation of apoptotic cells, demonstrating the importance of autophagosomes to this process. The signaling pathway led by the phagocytic receptor CED-1, the adaptor protein CED-6, and the large GTPase dynamin (DYN-1) promotes the recruitment of autophagosomes to phagosomes. Moreover, the subsequent fusion of autophagosomes with phagosomes requires the functions of the small GTPase RAB-7 and the HOPS complex components. Further observations suggest that autophagosomes provide apoptotic cell-degradation activities in addition to and in parallel of lysosomes. Our findings reveal that, unlike the single-membrane, LC3-associated phagocytosis (LAP) vesicles reported for mammalian phagocytes, the canonical double-membrane autophagosomes facilitate the clearance of C. elegans apoptotic cells. These findings add autophagosomes to the collection of intracellular organelles that contribute to phagosome maturation, identify novel crosstalk between the autophagy and phagosome maturation pathways, and discover the upstream signaling molecules that initiate this crosstalk. Probabilistic representations as building blocks for higher-level vision Current theories of perception suggest that the brain represents features of the world as probability distributions, but can such uncertain foundations provide the basis for everyday vision? Perceiving objects and scenes requires knowing not just how features (e.g., colors) are distributed but also where they are and which other features they are combined with. Using a Bayesian computational model, we recover probabilistic representations used by human observers to search for odd stimuli among distractors. Importantly, we found that the brain integrates information between feature dimensions and spatial locations, leading to more precise representations compared to when information integration is not possible. We also uncover representational asymmetries and biases, showing their spatial organization and arguing against simplified "summary statistics" accounts. Our results confirm that probabilistically encoded visual features are bound with other features and to particular locations, proving how probabilistic representations can be a foundation for higher-level vision. Action at a distance: Defects in division plane positioning in the root meristematic zone affect cell organization in the differentiation zone Cell division plane orientation is critical for plant and animal development and growth. TANGLED1 (TAN1) and AUXIN-INDUCED-IN-ROOT-CULTURES9 (AIR9) are division-site localized microtubule-binding proteins required for division plane positioning. tan1 and air9 Arabidopsis thaliana single mutants have minor or no noticeable phenotypes but the tan1 air9 double mutant has synthetic phenotypes including stunted growth, misoriented divisions, and aberrant cell-file rotation in the root differentiation zone. These data suggest that TAN1 plays a role in nondividing cells. To determine whether TAN1 is required in elongating and differentiating cells in the tan1 air9 double mutant, we limited its expression to actively dividing cells using the G2/M-specific promoter of the syntaxin KNOLLE (pKN:TAN1-YFP). Unexpectedly, in addition to rescuing division plane defects, pKN:TAN1-YFP rescued root growth and the root differentiation zone cell file rotation defects in the tan1 air9 double mutant. This suggests that defects that occur in the meristematic zone later affect the organization of elongating and differentiating cells.

Summary StatementExpression of TAN1 in the root meristematic zone rescues cell file rotation defects in tan1 air9 mutants, suggesting defects that occur in mitosis may influence organization of nondividing cells. Herbivore life histories are altered by drought stress in their hosts plants Drought associated with climate change can stress plants, altering their interactions with phytophagous arthropods. Dryness not only impacts cultivated plants but also their parasites, which in some cases are favoured by drought. Herbivorous arthropods feeding on drought-stressed plants typically produce bigger offspring and develop faster. However, how much responses to abiotic factors differ among populations of a species remains poorly documented. Here, we evaluate variability among populations of a major agricultural pest, the two spotted spider mite, Tetranychus urticae, in response to drought-stress. We compare key life-history parameters of twelve populations that originate from climates ranging from wet and cool Atlantic locations to medium to dry hot Mediterranean locations. We evaluated how plant drought stress affects four life history traits: development time, fecundity, sex-ratio and emigration rate in an experiment comparing well-watered and drought-stressed bean plants. Mites feeding on drought-stressed plants developed faster and attempted to leave leaves less often, and young females were more fecund. The mites from wet temperate climates exhibited greater plasticity between the two water regimes than mites originating from dryer and hot climates. Thus, climate in the area of origin influences mite response to drought. R7 photoreceptor axon targeting depends on the relative levels of lost and found expression in R7 and its synaptic partners As neural circuits form, growing processes select the correct synaptic partners through interactions between cell surface proteins. The presence of such proteins on two neuronal processes may lead to either adhesion or repulsion; however, the consequences of mismatched expression have rarely been explored. Here we show that the Drosophila CUB-LDL protein Lost and found (Loaf) is required in the UV-sensitive R7 photoreceptor for normal axon targeting only when Loaf is also present in its synaptic partners. Although targeting occurs normally in loaf mutant animals, removing loaf from photoreceptors or expressing it in their postsynaptic neurons Tm5a/b or Dm9 in a loaf mutant causes mistargeting of R7 axons. Loaf localizes primarily to intracellular vesicles including endosomes. We propose that Loaf regulates the trafficking or function of one or more cell surface proteins, and an excess of these proteins on the synaptic partners of R7 prevents the formation of stable connections. Statistical Analysis of Three-Dimensional Chromatin Packing Domains Determined by Chromatin Scanning Transmission Electron Microscopy (ChromSTEM) Chromatin organization over a wide range of length scales plays a critical role in the regulation of transcription and deciphering the interplay of these processes requires high-resolution, three-dimensional, quantitative imaging of chromatin structure in vitro. Herein, we introduce ChromSTEM, a method that utilizes high angle annular dark-field imaging and tomography in scanning transmission electron microscopy combined with DNA-specific staining for electron microscopy. We utilized ChromSTEM to quantify chromatin structure in cultured cells and the statistical packing behavior of the chromatin polymer. Using chromatin mass and density analysis, we observed that chromatin forms spatially well-defined higher-order domains which are around 100 nm in radius, with a radially decreasing mass-density from the center to the periphery. Although the morphological properties of the domains vary within the same cell line, they seem to exhibit greater heterogeneity across cell lines, underlying a potential role of statistical chromatin packing in regulating cell-type-specific gene expression. RESTORING GLUTAMATE RECEPTOR SIGNALING IN PANCREATIC ALPHA CELLS RESCUES GLUCAGON RESPONSES IN TYPE 1 DIABETES Glucagon secretion from pancreatic alpha cells is crucial to prevent hypoglycemia. For reasons still unknown, people with type 1 diabetes lose this glucoregulatory mechanism and are susceptible to dangerous hypoglycemia. Here we show that alpha cells in living pancreas slices from donors with type 1 diabetes failed to secrete glucagon in response to decreases in glucose concentration, thus mirroring the in vivo unresponsiveness to hypoglycemia. Glucagon content and responses to KCl depolarization were not affected, suggesting that alpha cells retained their secretory potential. By contrast, alpha cells had severely impaired signaling via glutamate receptors of the AMPA/kainate type. Under healthy conditions, activating these receptors was required to elicit full glucagon responses to decreases in glucose levels. In type 1 diabetes, reactivating residual glutamate receptor function with the positive allosteric modulators cyclothiazide and aniracetam restored glucagon secretion in response to hypoglycemia. These positive allosteric modulators are already approved to treat other conditions and could be repurposed to prevent hypoglycemia and improve management of diabetes. Omicron BA.2 specifically evades broad sarbecovirus neutralizing antibodies Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2s immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1-effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants. Effect of tag attachment on the flight performance of five raptor species Bio-logging devices play a fundamental and indispensable role in movement ecology studies, particularly in the wild. However, researchers are becoming increasingly aware of the influence that attaching devices can have on animals, particularly on their behaviour, energy expenditure and survival. The way a device is attached to an animals body has also potential consequences for the collected data, and quantifying the type and magnitude of such potential effects is fundamental to enable researchers to combine and compare data from different studies, as much as it is to improve animal welfare.

For over two decades, large terrestrial birds have been in the focus of long-term movement ecology research, employing bio-logging devices attached with different types of harnesses. However, comparative studies investigating the effects of different harness types used on these species are scarce.

In this study, we tested for potential differences in data collected by two commonly used harness types, backpack and leg-loop, on the flight performance of 10 individuals from five raptor species, equipped with high resolution bio-logging devices, in the same area and time. We explored the effect of harness type on vertical speed, horizontal speed, glide ratio, height above sea level, distance travelled, proportion of soaring and flapping behaviour, and VeDBA (a proxy for energy expenditure) between and within individuals, all used as fine-scale measures of flight performance. Birds equipped with leg-loops climbed up to 0.65 ms-1 faster, reached 19% greater heights while soaring, and spent less time in active flight compared to birds equipped with backpacks, suggesting that backpack harnesses, compared to leg-loops, might cause additional drag affecting the birds flight performance. A lower rate of sinking while gliding, a slightly higher glide ratio, higher horizontal speed while soaring, and lower VeDBA, were also indicative of less drag using leg-loops. Our results add to the existing literature highlighting the design-related advantages of leg-loops, and support the use of leg-loops as a better alternative to backpack harnesses for large soaring birds, when possible. Our study also highlights how apparently small changes in device attachment can lead to notable improvements in tagging practice, with implications for animal welfare, data interpretation and comparability. Centimeter-scale quorum sensing dictates collective survival of differentiating embryonic stem cells Cells can help each other replicate by communicating with diffusible molecules. In cell cultures, molecules may diffuse within a cell colony or between adjacent or distant colonies. Determining which cell helps which cells replication is challenging. We developed a systematic approach, integrating modeling and experiments, for determining the length-scales of cell-cell communication (from microns to centimeters). With this approach, we discovered that differentiating murine ES cells, scattered across centimeters on a dish, communicate over millimeters to form one macroscopic entity that survives if and only if its centimeter-scale population-density is above a threshold value. Single-cell-level measurements, transcriptomics, and modeling revealed that this "macroscopic quorum sensing" arises from differentiating ES cells secreting and sensing survival-promoting FGF4 that diffuses over millimeters and activates YAP1-induced survival mechanisms. Through the same mechanism, a lone macroscopic, but not microscopic, colony survives differentiation. Our work rigorously establishes that in vitro ES-cell differentiation relies on macroscopic cooperation. From fitting the average to fitting the individual: A cautionary tale for mathematicalmodelers An outstanding challenge in the clinical care of cancer is moving from a one-size-fits-all approach that relies on population-level statistics towards personalized therapeutic design. Mathematical modeling is a powerful tool in treatment personalization, as it allows for the incorporation of patient-specific data so that treatment can be tailor-designed to the individual. Herein, we work with a mathematical model of murine cancer immunotherapy that has been previously-validated against the average of an experimental dataset. We ask the question: what happens if we try to use this same model to perform personalized fits, and therefore make individualized treatment recommendations? Typically, this would be done by choosing a single fitting methodology, and a single cost function, identifying the individualized best-fit parameters, and extrapolating from there to make personalized treatment recommendations. Our analyses show the potentially problematic nature of this approach, as predicted personalized treatment response proved to be sensitive to the fitting methodology utilized. We also demonstrate how a small amount of the right additional experimental measurements could go a long way to improve consistency in personalized fits. Finally, we show how quantifying the robustness of the average response could also help improve confidence in personalized treatment recommendations.

Author summaryAs we enter the era of healthcare where personalized medicine becomes a more common approach to treating cancer patients, harnessing the power of mathematical models will only become more essential. Using a preclinical dataset on cancer immunotherapy, we explore the challenges and limitations that arise when trying to move from fitting and making predictions for the population-level average, to fitting and making predictions for an individual. We find that the standard of approach of picking a single fitting methodology and a single cost function may end up having limited predictive value when applied to individual data. We also show how having a small amount of the right additional experimental data, and establishing the robustness of average treatment response, can help improve confidence in personalized model predictions.