Miracle-dz/UniFAR-FTUs huggingface dataset:
A Visual, Inexpensive, and Wireless Capillary Rheometer

Complex fluid systems can exhibit highly non-linear and time-dependent flow behaviors that arise from microscale reorganization. Rheological measurements to understand these flow-induced properties in soft condensed matter and biology are critical to optimize manufacturing processes that rely upon the use of complex fluids, such as the creation of viscoelastic bioinks for 3D bioprinting. While typical rheological characterizations are performed on bulky and expensive rheometers, these options do not readily enable in situ microscopic visualization of flow behavior, which can provide microstructural insights into the mechanisms and patterns of yielding. To address these limitations, we present a visual, inexpensive (approximately $200), and wireless capillary rheometer (VIEWR) assembled from chiefly 3D printed components. We validate the accuracy and reliability of the portable rheometer by comparing measurements of multiple rheological parameters, including viscosity and yield stress, with measurements obtained from a commercial oscillatory rheometer. At its core, VIEWR employs an easily interchangeable glass capillary channel to enable real-time microscopic observation under flow conditions. To facilitate various experimental conditions, a communication protocol based on Internet of Things (IoT) is adapted to support wireless transmission of data. This unique rheometer design can be used for characterizing and visualizing numerous living and non-living complex fluids. Specifications table
The genetic basis for adaptation in giant sea anemones to their symbiosis with anemonefish and Symbiodiniaceae

Sea anemones in the order Anthozoa play an integral part in marine ecosystems by providing refuge and habitat for various organisms. Despite this, much of their molecular ecology remains elusive. Sea anemones can nurture numerous symbiotic relationships; the most iconic being the one between giant sea anemones and anemonefish. However, the genes and biological processes associated with this symbiosis in the sea anemones in unknown. Additionally, it is unclear how genes can mediate interactions between sea anemones, anemonefish, and symbionts from the algal family Symbiodiniaceae. Here we compared the gene expression profiles of tentacles from several cnidarians to uncover the genetic basis for adaptations in giant sea anemones to their symbiosis with anemonefish and Symbiodiniaceae. We found that tentacle transcriptomes of cnidarians are highly diverse, with closely related species having more similar expression patterns. However, despite an overall high correlation between gene expression and phylogeny, the giant sea anemones showed distinct expression patterns. The giant sea anemones had gene co-expression clusters enriched for processes involved in nutrient exchange and metabolism. These genes were not only differentially expressed, but also experienced evolutionary shifts in expression in giant sea anemones. Using a phylogenetic multilevel model, we found that Symbiodiniaceae and anemonefish significantly affect gene expression in giant sea anemone tentacles. By characterizing gene expression patterns, we identify genes and biological processes that provide evidence for the cross-talk between Symbiodiniaceae, anemonefish, and giant sea anemones. Our study demonstrates how integrated biological processes can lead to the evolution of a successful multi-organism interaction.
The RNA binding proteins ZFP36L1 and ZFP36L2 modulate transcriptional and post-transcriptional genome-wide effects of glucocorticoids

Glucocorticoids (GCs) are one of the most used anti-inflammatory drugs worldwide. Despite their widespread use, our understanding of their post-transcriptional effects remains poorly understood. The tristetraprolin (TTP) RNA binding protein (RBP) family (ZFP36, ZFP36L1 and ZFP36L2) has been implicated in inflammation regulation via binding to AU-rich elements (ARE) in mRNAs, with TTP being implicated in GC modulation. We hypothesised that ZFP36L1 and ZFP36L2 are part of the GC pathway and tested this hypothesis in bronchial epithelium, which commonly encounters GC in vivo upon inhalation. Our data show that dexamethasone, a commonly used GC, modulated the levels, subcellular localisation and RNA binding of ZFP36L1/L2. Employing Frac-seq (subcellular fractionation and RNA-sequencing), we show that GC modulated distinct subsets of RNAs in a subcellular-dependent manner. In addition to their mostly known transcriptional effects (116 differentially expressed genes, DEGs), GCs modified the binding to monosomes of myriad mRNAs (83 differentially bound genes, DBGs). We also demonstrate that ZFP36L1/L2 modulated gene expression mainly at the total cytoplasmic and polyribosome binding levels. ZFP36L1/L2 down-regulation led to an increase in ARE-containing mRNAs and a pronounced modification of the effects of GC on gene expression. We observed a small overlap of genes modulated by GCs when comparing control and ZFP36L1/L2 knockdown cells, in a subcellular-dependent manner Our data also suggest a novel role for these RBPs and GCs in epithelial biology via regulation of mRNAs encoding proteins important for epithelial cell function including cellular structure. We believe that our data has further implications in how we investigate gene expression. We show the power of employing sub-cellular fractionation when analysing genome-wide effects for known ‘transcriptional modulators’ such as GCs, as well as a tool to demonstrate the extent of the effect of RBPs on gene expression modulation beyond total RNA levels.
Quantum frequency estimation with trapped ions and atoms

We discuss strategies for quantum-enhanced estimation of atomic transition frequencies with ions stored in Paul traps or neutral atoms trapped in optical lattices. We show that only marginal quantum improvements can be achieved using standard Ramsey interferometry in the presence of collective dephasing, which is the major source of noise in relevant experimental setups. We therefore analyze methods based on decoherence free subspaces and prove that quantum enhancement can readily be achieved even in the case of significantly imperfect state preparation and faulty detections.
Rapid response of fly populations to gene dosage across development and generations

Although the effects of genetic and environmental perturbations on multicellular organisms are rarely restricted to single phenotypic layers, our current understanding of how developmental programs react to these challenges at a systems level remains limited. Here, we have examined the phenotypic consequences of disturbing the classic bicoid network in Drosophila, which is essential for anterior-posterior patterning in the early embryo. This network can be synthetically perturbed by increasing the dosage of bicoid, which causes a posterior shift of the network’s regulatory outputs and a decrease in fitness. To directly monitor network changes across populations and time with extra copies of bicoid, we performed genome-wide EMS mutagenesis, followed by experimental evolution. After only 8-15 generations, experimental populations have normalized patterns of gene expression and increased survival. Using a phenomics approach, we find that populations were normalized through rapid increases in embryo size driven by maternal changes in metabolism and ovariole development. We extend our results to additional populations of flies, demonstrating predictability. Together, our results necessitate a broader view of regulatory network evolution at the systems level. In the future, such synthetic evolution approaches using animal models could provide a generalizable platform for studying the propagation of genetic perturbations across the many layers of complex multicellular systems.
Goal-directed vocal planning in a songbird

Songbirds’ vocal mastery is impressive, but to what extent is it a result of practice? Can they, based on experienced mismatch with a known target, plan the necessary changes to recover the target in a practice-free manner without intermittently singing? In adult zebra finches, we drive the pitch of a song syllable away from its stable (baseline) variant acquired from a tutor, then we withdraw reinforcement and subsequently deprive them of singing experience by muting or deafening. In this deprived state, birds do not recover their baseline song. However, they revert their songs towards the target by about one standard deviation of their recent practice, provided the sensory feedback during the latter signaled a pitch mismatch with the target. Thus, targeted vocal plasticity does not require immediate sensory experience, showing that zebra finches are capable of goal-directed vocal planning.
Disruption of Tonic Endocannabinoid Signaling Triggers the Generation of a Stress Response

Endocannabinoid (eCB) signalling gates many aspects of the stress response, including the hypothalamic-pituitary-adrenal (HPA) axis. The HPA axis is controlled by corticotropin releasing hormone (CRH) producing neurons in the paraventricular nucleus of the hypothalamus (PVN). Disruption of eCB signalling increases drive to the HPA axis, but the mechanisms subserving this process are poorly understood. Using an array of cellular, endocrine and behavioral readouts associated with activation of CRH neurons in the PVN, we evaluated the contributions of tonic eCB signaling to the generation of a stress response. The CB1 receptor antagonist/inverse agonist AM251, neutral antagonist NESS243, and NAPE PLD inhibitor LEI401 all uniformly increased c-fos in the PVN, unmasked stress-linked behaviors, such as grooming, and increased circulating CORT, recapitulating the effects of stress. Similar effects were also seen after direct administration of AM251 into the PVN, while optogenetic inhibition of PVN CRH neurons ameliorated stress-like behavioral changes produced by disruption of eCB signaling. These data indicate that under resting conditions, constitutive eCB signaling restricts activation of the HPA axis through local regulation of CRH neurons in the PVN.
DomainRank: Improving Biological Data Sets With Domain Knowledge and Google’s PageRank

Motivation The quality of biological data crucially affects progress in science. This quality can be improved with better measurement devices, more sophisticated experimental designs, or repetitious measurements. Each of these options is associated with substantial costs. We present a simple computational tool as an alternative. This algorithmic tool, called DomainRank, leverages simple domain knowledge and overlapping information content in biological network data to improve measurement quality at a negligible cost. Following the simple computational template of Domain-Rank, researchers can boost the confidence of their own data with little effort. Results We demonstrate the performance of DomainRank in three test cases: DomainRank finds 14.9% more interactions in quantitative proteomics experiments, improves the precision of predicted residue-residue contacts from co-evolutionary data by up to 11.6% (averaged over 882 proteins), and identifies 89.2% more cross-links in photo-crosslinking/mass spectrometry (photo-CLMS) experiments. Although our proposed template is specialized on biological network data, we view this approach as an universal computational tool for data improvement that could be routinely applied in many disciplines. Availability An implementation of DomainRank is freely available: https://github.com/Rappsilber-Laboratory/pagerank-refine
The Arabidopsis SHORTROOT network coordinates shoot apical meristem development with auxin-dependent lateral organ initiation

Unlike animals, plants have the capacity to produce new organs post-embryonically throughout their entire life cycle. This is due to stem cells present in the shoot and the root apical meristems (SAM and RAM, respectively). In the SAM, stem cells are located in the central zone (CZ) where they divide slowly. Stem cell daughters are displaced laterally and enter the peripheral zone (PZ). Here, their mitotic activity increases, and lateral organ primordia (LOP) are formed. How the spatial arrangement of these different domains is initiated and controlled during SAM growth and development, and how sites of LOP are determined in the PZ is not yet completely understood. In the RAM, the GRAS family transcription factor SHORTROOT (SHR) acts as a master regulator of signalling pathways that maintain the root stem cell niche and control formation of ground tissue layers. We hypothesized that SHR could perform a similar role in the SAM, and found that SHR, together with its target transcription factors SCARECROW (SCR), SCARECROW-LIKE23 (SCL23) and JACKDAW (JKD), controls shoot meristem size by regulating cell division rates, and promotes formation of lateral organs. SHR, SCR, SCL23 and JKD are expressed in very distinct patterns in the SAM. Where these expression domains overlap, they can physically interact to activate expression of the key cell cycle regulator CYCLIND6;1 (CYCD6;1) and thereby promote the formation of new cell layers. In the PZ, upregulation of SHR expression at sites of organ initiation depends on the phytohormone auxin, acting through the auxin response factor MONOPTEROS (MP) and auxin response elements in the SHR promoter. In the CZ, the SHR-target SCL23 physically interacts with WUS, a key regulator of stem cell maintenance, and both SCL23 and WUS expression are subject to negative feedback regulation from stem cells through the CLAVATA signalling pathway. Together, our findings illustrate how SHR-dependent transcription factor complexes act in different domains of the shoot meristem to mediate cell division and auxin dependent organ initiation in the PZ, and coordinate this activity with stem cell maintenance in the CZ of the SAM.
A computational understanding of zoomorphic perception in the human brain

It is common to find objects that resemble animals on purpose (e.g., toys). While the perception of such objects as animal-like seems obvious to humans, such “Animal bias” for zoomorphic objects turned out to be a striking discrepancy between the human brain and artificial visual systems known as deep neural networks (DNNs). We provide a computational understanding of the human Animal bias. We successfully induced this bias in DNNs trained explicitly with zoomorphic objects. Alternative training schedules, focusing on previously identified differences between the brain and DNNs, failed to cause an Animal bias. Specifically, we considered the superordinate distinction between animate and inanimate classes, the sensitivity for faces and bodies, the bias for shape over texture, and the role of ecologically valid categories. These findings provide computational support that the Animal bias for zoomorphic objects is a unique property of human perception yet can be explained by human learning history.
Influenza A virus reassortment is strain dependent

RNA viruses can exchange genetic material during coinfection, an interaction that creates novel strains with implications for viral evolution and public health. Influenza A viral genetic exchange occurs when genome segments from distinct strains reassort in coinfection. Predicting potential reassortment between influenza strains is a longstanding goal. Experimental coinfection studies have shed light on factors that limit or promote reassortment. However, determining the reassortment potential between diverse Influenza A strains has remained an elusive goal. To fill this gap, we developed a high throughput genotyping approach to quantify reassortment among a diverse panel of human influenza virus strains, encompassing 41 years of epidemics, multiple geographic locations, and both circulating human subtypes A/H1N1 and A/H3N2. We found that the reassortment rate (proportion of reassortants) is an emergent property of a pair of strains where strain identity is a predictor of the reassortment rate. We show little evidence that antigenic subtype drives reassortment as intersubtype (H1N1xH3N2) and intrasubtype reassortment rates were, on average, similar. Instead, our data suggest that certain strains bias the reassortment rate up or down, independently of the coinfecting partner. We also observe that viral productivity is an emergent property of coinfections and that it is not correlated to reassortment rate, thus affecting the total number of reassortant progeny produced. Assortment of individual segments among progeny, and pairwise segment combinations within progeny, were not random and generally favored homologous combinations. This outcome was not related to strain similarity or shared subtype. Reassortment rate was closely correlated to both the proportion of unique genotypes and the proportion of progeny with heterologous pairwise segment combinations. We provide experimental evidence that viral genetic exchange is potentially an individual social trait subject to natural selection, which implies the propensity for reassortment is not evenly shared among strains. This study highlights the need for research incorporating diverse strains to discover the traits that shift the reassortment potential as we work towards the goal of predicting influenza virus evolution resulting from segment exchange.
Operational Gene Clusters and intrinsic uncertainty in pangenome analyses

19 A key step for comparative genomics is to group open reading frames into functionally and 20 evolutionarily meaningful gene clusters. Such clustering is complicated by intraspecific gene 21 duplications and horizontal gene transfers, that are frequent in prokaryotes. In consequence, gene 22 clustering methods must deal with a trade-off between identifying vertically transmitted 23 representatives of multi-copy gene families (recognizable by synteny conservation) and retrieving 24 complete sets of species-level orthologs. We studied the conceptual and practical implications of 25 adopting homology, orthology, or synteny conservation as formal criteria for gene clustering by 26 performing comparative analyses of 125 prokaryotic pangenomes. We found that clustering criteria 27 affect pangenome functional characterization, core genome inference, and reconstruction of 28 ancestral gene content to different extents. Pangenome and core genome sizes are affected by the 29 same multiplicative factor in all species, which allows for robust across-species comparisons 30 regardless of the clustering criterion. However, across-species comparisons of pangenome diversity, 31 gene fluxes, and functional profiles are substantially affected by inconsistencies among clustering 32 criteria. Such inconsistencies are driven not only by mobile genetic elements, but also by genes 33 involved in defense, secondary metabolism, and other functions overrepresented in the accessory 34 genome. In the case of pangenome diversity, the variability that can be attributed to methodological 35 inconsistencies can exceed the effect sizes of ecological and phylogenetic variables. Our results 36 emphasize the need to consider conceptual adequacy, not just computational performance, when 37 designing workflows for pangenome analysis. We also provide a benchmarking dataset to assess the 38 robustness and across-method reproducibility of future comparative studies. 39
Development shaped by cue reliability in the barn owl’s auditory midbrain

Sensory systems display capability to preferentially choose stimuli based on their reliability at conveying accurate information. While previous reports have shown the ability of the brain to reweigh cues based on ongoing or dynamic changes in reliability, how the brain may learn and maintain neural responses to sensory statistics expected to be stable over longer time periods remain significant open questions of potential mechanisms underlying naturalistic biased perception. This study provides evidence that the barn owl’s midbrain is shaped by permanent statistics experienced during development. The barn owl’s midbrain features a topographic map of auditory space where neurons compute horizontal sound location from the interaural time difference (ITD). Previous work has shown that frequency tuning of these midbrain map neurons is correlated with the pattern of most reliable frequencies for the neurons’ preferred ITD. This pattern of ITD reliability is due to the filtering properties of the head, primarily determined by the facial ruff in the barn owl. In this study, we found that the absence of a facial ruff led to a decrease in the reliability of high frequencies originating from frontal space. To test if the owl’s frequency tuning of midbrain map neurons is driven by permanent changes in the pattern of ITD reliability, these neurons were recorded from adult owls, who had the facial ruff removed as juveniles, and from juvenile owls, before the facial ruff developed. In both groups, we found that frontally-tuned neurons displayed tunings to frequencies lower than reported in normal adult owls, consistent with the difference in ITD reliability between the normal and ruff removed conditions. Juvenile owls also exhibited more heterogeneous frequency tuning, suggesting developmental processes that refine tuning to match the pattern of ITD reliability. Additional recordings immediately upstream of the midbrain map displayed ITD tuned neural responses for all frequencies across the owl’s normal hearing range. Broader analysis of the effects of ruff-removal on the acoustical properties of spatial cues indicated a dominant role of ITD reliability in driving the adaptive changes in frequency tuning. These results support the hypothesis that frequency tuning in the midbrain map is developmentally adapted to permanent statistics of spatial cues, implementing probabilistic coding for sound localization.
Extremely low sample size allows age and growth estimation in a rare and threatened shark

Understanding life history parameters is key to assessing biological productivity, extinction risk, and informing the management of exploited fish populations. Age-and-growth analyses in chondrichthyan fishes (sharks, rays, and ghost sharks) is primarily undertaken through counting band pairs laid down in vertebrae. For rare, threatened, and protected species such as river sharks (family Carcharhinidae; genus Glyphis) of northern Australia, obtaining sufficient samples of vertebrae may not be possible. Here we use a very sample size, selective size-class sampling, and back-calculation techniques to provide age and growth data on the Speartooth Shark Glyphis glyphis from which comprehensive sampling is not possible. Ten individuals were sampled from the Adelaide River, Northern Territory, Australia. Length-at-age models were applied to the observed and back-calculated data with the sexes combined due to the small sample size and growth estimated using a multi-model framework. Band pair counts produced age estimates of 0–11 years. Most model parameter estimates for length-at-birth (L0) and asymptotic length (L∞) were biologically plausible. The model averaged parameters for the observed data were total length (TL) and TL, and for back-calculated data were TL and TL. Overall, the parameter standard errors and model residual standard errors were lower for the back-calculated data due to the addition of interpolated data. Analysed samples were restricted to juveniles and sub-adults as adult G. glyphis have not been encountered in the Northern Territory. The ageing results suggest an age-at-maturity of >12 years for this species. The lack of mature individuals in the sample means that this analysis should be considered as a partial growth curve with length-at-age estimates that are valid over the available age range. The results presented here provide the first age and growth estimation for river sharks.