Reduction of protein disulfide isomerase results in open conformations and stimulates dynamic exchange between structural ensembles Protein disulfide isomerase (PDI) is a ubiquitous redox-regulated enzyme that interacts with hundreds of client proteins intracellularly and extracellularly. It comprises two redox-sensitive domains, each hosting the conserved catalytic motif CxxC, two redox-insensitive protein-binding domains, and three linkers. Snapshots of oxidized and reduced PDI have been obtained by X-ray crystallography. Yet, how PDIs structure dynamically changes in response to the redox microenvironment and ligand binding remain unknown. Here, we used multiparameter confocal single-molecule Forster resonance energy transfer (smFRET) and multiple FRET pairs to track the movements of the two catalytic domains with high temporal resolution. Our studies document that, at equilibrium, PDI visits three structurally distinct conformational ensembles, two "open" (O1 and O2) and one "closed" (C). We show that the redox environment dictates the time spent in each ensemble and the rate at which they exchange. While oxidized PDI samples O1, O2 and C more evenly and in a slower fashion, reduced PDI predominantly populates O1 and O2, and exchanges between them more rapidly, on the sub-millisecond timescale. These findings were not expected based on crystallographic data. Using mutational analyses, we further demonstrate that the two active sites are structurally nonequivalent and that ligands targeting the active sites of reduced PDI shift the equilibrium towards closed conformations of the enzyme. This work introduces a new structural framework that challenges current views of PDI dynamics, helps rationalize the multifaced role of PDI in biology and may assist drug development.
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.
Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Tracing back variations in archaeal cell division to protein domain architectures The Endosomal Sorting Complex Required for Transport (ESCRT) system is a multi-protein machinery that is involved in cell division of both Eukaryotes and Archaea. This spread across super-phyla suggests that a precursor ESCRT machinery existed already at an evolutionary early stage of life, making it a promising candidate for the (re)construction of a minimal cell division machinery. There are, however, only few experimental data about ESCRT machineries in Archaea, due to high technical challenges in cultivation and microscopy. Here, we analyse the proteins of archaeal ESCRT machineries bioinformatically on a domain level, to enable mechanistical comparison without such challenging experiments. First, we infer that there are at least three different cell division mechanisms utilizing ESCRT proteins in archaea, probably similar in their constriction mechanisms but different in membrane tethering. Second, we show that ESCRT proteins in Asgard archaea are highly similar to eukaryotic ESCRT proteins, strengthening the recently developed idea that all Eukaryotes descended from archaea. Third, we reconstruct a plausible evolutionary development of ESCRT machineries and suggest that a simple ESCRT-based constriction machinery existed in the last archaeal common ancestor. These findings not only give very interesting insights into the evolution of cell division in Archaea and Eukaryotes, but also reveal new research avenues by suggesting hypothesis-driven experiments for both, cell biology and bottom-up synthetic biology. Experimental evolution reveals post-transcriptional regulation as a novel driver of Leishmania fitness gain The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein abundance linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in abundance of flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain in culture, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania transcriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings. PlotMI: interpretation of pairwise dependencies and positional preferences learned by deep learning models from sequence data Deep learning models have recently gained success in various tasks related to understanding information coded in biological sequences. Although offering state-of-the art predictive performance, the predictions made by deep learning models can be difficult to understand. In virtually all biological research, the understanding of how a predictive model works is as, or even more important as the raw predictive performance. Thus interpretation of deep learning models is an emerging hot topic especially in context of biological research. Here we describe PlotMI, a mutual information based model interpretation tool that can intuitively visualize positional preferences and pairwise dependencies learned by any machine learning model trained on sequence data such as DNA, RNA or amino acid sequence. PlotMI can also be used to compare dependencies present in training data to the dependencies learned by the model and to compare dependencies learned by different types of models that are trained to perform the same task. PlotMI is freely available at https://github.com/hartonen/plotMI. Glypiated FGF directs contact-mediated bidirectional signaling to self-regulate tissue-specific dispersion How signaling proteins generate a multitude of information to organize tissue patterns is critical to understanding morphogenesis. In Drosophila, FGF produced in wing-disc cells regulates the development of the disc-associated air-sac-primordium (ASP). Here, we show that FGF is Glycosylphosphatidylinositol-anchored to the producing cell surface and that this modification both inhibits free FGF secretion and activates target-specific bidirectional FGF-FGFR signaling through cytonemes. FGF-source and recipient ASP cells extend cytonemes that present FGF and FGFR on their surfaces and reciprocally recognize each other over distance by contacting through CAM-like FGF-FGFR binding. Contact-mediated FGF-FGFR binding induces bidirectional signaling, which, in turn, promotes ASP and source cells to polarize cytonemes toward each other and reinforce signaling contacts. Subsequent un-anchoring of FGFR-bound-FGF from the source cell membrane dissociates cytoneme contacts and delivers FGF target-specifically to ASP cytonemes for paracrine functions. Thus, GPI-anchored FGF organizes both source and recipient cells and self-regulates its cytoneme-mediated tissue-specific dispersion and signaling. Structural predictions of the SNX-RGS proteins suggest they belong to a new class of lipid transfer proteins Recent advances in protein structure prediction using machine learning such as AlphaFold2 and RosettaFold presage a revolution in structural biology. Genome-wide predictions of protein structures are providing unprecedented insights into their architecture and intradomain interactions, and applications have already progressed towards assessing protein complex formation. Here we present detailed analyses of the sorting nexin proteins that contain regulator of G-protein signalling domains (SNX-RGS proteins), providing a key example of the ability of AlphaFold2 to reveal novel structures with previously unsuspected biological functions. These large proteins are conserved in most eukaryotes and are known to associate with lipid droplets (LDs) and sites of LD-membrane contacts, with key roles in regulating lipid metabolism. They possess five domains, including an N-terminal transmembrane domain that anchors them to the endoplasmic reticulum, an RGS domain, a lipid interacting phox homology (PX) domain and two additional domains named the PXA and PXC domains of unknown structure and function. Here we report the crystal structure of the RGS domain of sorting nexin 25 (SNX25) and show that the AlphaFold2 prediction closely matches the experimental structure. Analysing the full-length SNX-RGS proteins across multiple homologues and species we find that the distant PXA and PXC domains in fact fold into a single unique structure that notably features a large and conserved hydrophobic pocket. The nature of this pocket strongly suggests a role in lipid or fatty acid binding, and we propose that these molecules represent a new class of conserved lipid transfer proteins. The compound of baicalein, wogonin, and oroxylin-A inhibiting EMT in A549 cell line via PI3K/AKT-TWIST1-glycolysis pathway Non-small cell lung cancer (NSCLC) is a worldwide disease with high morbidity and mortality, which is most derived from its metastasis. Some researches show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cells migration and invasion, leading to NSCLC metastasis. Total Flavonoid Aglycones Extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds (baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)), the reconstructed TFAE (reTFAE) present inhibitory effect on the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC. Mouse lemur, a new primate model to investigate cardiac pacemaker activity. BackgroundGray mouse lemurs (Microcebus murinus) are one of the smallest and most ancestral primates known. Their size falls in between that of mice and rats, and their genetic proximity to humans makes them an emerging model to study age-related neurodegeneration. Since Microcebus murinus replicates similar senescence processes of humans, it constitutes a useful model also for studying cardiovascular dysfunctions. However, its cardiac physiology is unknown. Thus, we investigated sinoatrial node (SAN) pacemaker activity of mouse lemurs, presenting the first characterization of heart automaticity in nonhuman primates.

Methods and ResultsWe recorded the heart automaticity in freely moving mouse lemurs and in their SAN tissues and pacemaker myocytes. Mouse lemurs have a heart rate (HR) in between those of mice and rats and a similar generation of electrical impulses in the SAN tissue. Conversely, their ventricular depolarization is more similar to large mammals. Mouse lemur SAN myocytes express the main pacemaker currents at densities similar to mice: the hyperpolarization-activated current (If) and the L-type (ICa,L) and T-type (ICa,T) calcium currents. Moreover, mouse lemur SAN myocytes display spontaneous ryanodine receptor (RyR)-dependent Ca2+ transients. Using muscle-derived stem cells (MDSCs) from the Microcebus murinus skeletal muscle, we also differentiated pacemaker-like (PML) cells showing spontaneous automaticity and expressing markers of native SAN myocytes (HCN4 and connexin-45).

ConclusionsIn conclusion, our characterization of heart automaticity in Microcebus murinus provides new opportunities for comparative cardio-physiology studies in primates and with humans, and for pharmacologic testing of molecules that could assist in modulating age-related dysfunctions of automaticity. Curation, inference, and assessment of a globally reconstructed gene regulatory network for Streptomyces coelicolor Streptomyces coelicolor A3(2) is a model microorganism for the study of Streptomycetes, antibiotic production, and secondary metabolism in general. Even though S. coelicolor has an outstanding variety of regulators among bacteria, little effort to globally study its transcription has been made. We manually curated 29 years of literature and databases to assemble a meta-curated experimentally-validated gene regulatory network (GRN) with 5386 genes and 9707 regulatory interactions ([~]41% of the total expected interactions). This provides the most extensive and up-to-date reconstruction available for the regulatory circuitry of this organism. Only [~]6% (534/9707) are supported by experiments confirming the binding of the transcription factor to the upstream region of the target gene, the so-called "strong" evidence. While for the remaining interactions there is no confirmation of direct binding. To tackle network incompleteness, we performed network inference using several methods (including two proposed here) for motif identification in DNA sequences and GRN inference from transcriptomics. Further, we contrasted the structural properties and functional architecture of the networks to assess the reliability of the predictions, finding the inference from DNA sequence data to be the most trustworthy approach. Finally, we show two applications of the inferred and the curated networks. The inference allowed us to propose novel transcription factors for the key Streptomyces antibiotic regulatory proteins (SARPs). The curated network allowed us to study the conservation of the system-level components between S. coelicolor and Corynebacterium glutamicum. There we identified the basal machinery as the common signature between the two organisms. The curated networks were deposited in Abasy Atlas (https://abasy.ccg.unam.mx/) while the inferences are available as Supplementary Material. Haplotype-resolved powdery mildew resistance loci reveal the impact of heterozygous structural variation on NLR genes in Muscadinia rotundifolia Muscadinia rotundifolia cv. Trayshed is a valuable source of resistance to grape powdery mildew. It carries two powdery mildew resistance-associated genetic loci, Run1.2 on chromosome 12 and Run2.2 on chromosome 18. In this study, we identified, phased, and reconstructed the two haplotypes of each resistance-associated locus. Haplotype phasing allowed the identification of several structural variation events between haplotypes of both loci. Combined with manual refinement of the gene models, we found that the heterozygous structural variants affected the gene content, with some resulting in duplicated or hemizygous nucleotide-binding leucine-rich repeat (NLR) genes. Structural variations also impacted the domain composition of some NLRs. These findings emphasize the need of generating haplotype-resolved sequences instead of using consensus sequences for identifying haplotype-specific candidate genes. Comparison of the NLRs in the Run1.2 and Run2.2 loci indicated that the two loci are composed of a different number and classes of NLR genes. We provide a list of candidate NLR genes from the Run1.2b and Run2.2 loci, whose expression suggests a role in powdery mildew resistance in Trayshed. These first complete and haplotype-resolved resistance-associated loci, and their candidate NLR genes, represent new resources to develop powdery mildew-resistant grape cultivars. Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. A platform of patient-derived microtumors identifies therapeutic vulnerabilities in ovarian cancer. BackgroundIn light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems representing patient tumor heterogeneity, while enabling parallel drug testing and identification of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease with complex microenvironment and high recurrence rates, we developed a 3D preclinical ovarian cancer model comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) for identification of treatment vulnerabilities and validation of anti-cancer drug efficacy using immunohistochemistry, immune cell phenotyping, functional assays and protein profiling analyses.

MethodsPDM and TILs were isolated from fresh primary ovarian cancer tissue specimen using mechanical disruption and limited enzymatic digestion and were subsequently cultured in suspension in defined media in the absence of serum. The heterogeneous cellular composition of isolated PDM as well as autologous TILs was analyzed by FFPE immunohistochemistry and multi-color flow cytometry, respectively. For in-depth protein profiling of PDM we established Reverse Phase Protein Array (RPPA) analyses of >110 total and phospho-proteins. Treatment efficacy in response to chemotherapeutics as well as immunotherapeutic compounds was assessed in PDM and PDM-TIL co-cultures using a functional viability assay in microplate format.

ResultsThe enzymatic digestion of primary ovarian cancer tissue and suspension culture in defined serum-free media allowed fast and efficient recovery of patient-derived microtumors (PDM). Immunohistochemical analyses demonstrated histopathological comparability of ovarian cancer PDM with corresponding patient tumor tissue. Reverse Phase Protein Array (RPPA)-based analyses of >110 total and phospho-proteins enabled the identification of patient-specific sensitivities to standard, platinum-based therapy and thereby the prediction of potential treatment-responders. Finally, combining PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitor treatment demonstrated the potential for patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach.

Conclusion3D patient-derived ovarian cancer microtumors represent a preclinical, ex vivo tumor model that reflects intertumoral heterogeneity and represent the cellular complexity of individual patient tumors. Combining protein pathway analysis and anti-cancer drug efficacy testing of PDM enables drug mode-of-action analyses and therapeutic sensitivity prediction within a clinically relevant time frame after surgery. Follow-up studies in larger cohorts are currently under way to further evaluate the applicability of this platform to support clinical decision-making and personalizing cancer treatment. 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. Development of an in-situ printing system with human platelet lysate-based bio-adhesive to treat corneal perforation PurposeCorneal perforation is a clinical emergency. Tissue glue to seal the perforation, and supplementary topical medication represents existing standard treatment. Previously, our group developed a transparent human platelet lysate (hPL)-based biomaterial that showed good cell compatibility and accelerated corneal epithelial cells healing in-vitro. This study aims to develop a novel treatment method for corneal perforation using this biomaterial.

MethodsRheometry was used to measure the hPL-based biomaterial behaviour at room and corneal surface temperatures. Its adhesiveness to porcine skin and burst pressure limit were also measured. Based on rheological behaviour, a hand-held biopen was developed to extrude it onto the cornea. An animal trial (5 New Zealand white rabbits) to compare impact of the biomaterial and cyanoacrylate glue (control group) on a 2mm perforation was conducted to evaluate safety and efficacy.

ResultsThe hPL-based biomaterial showed higher adhesiveness compared to commercial fibrin glue and withstood burst pressure approximately 6.4x higher than routine intraocular pressure. Treatment rabbits had lower pain scores and faster recovery, despite generating similar scar-forming structure compared to controls. No secondary corneal ulcer was generated in rabbits treated with the bio-adhesive.

ConclusionsThis study reports a novel in-situ printing system capable of delivering a hPL-based, transparent bio-adhesive and successfully treating small corneal perforations. Bio-adhesive-treated rabbits recovered faster and required no additional analgesia. Both groups showed scarred corneal tissue after healing, however no infection and inflammation was observed by 3 weeks. The delivery system was easy to use and may represent an alternative treatment for corneal perforation.

HighlightsO_LIThis study presents a novel in situ printing system to treat corneal perforation
C_LIO_LIThe system is comprised of a human platelet lysate-based bio-adhesive and a pen-like hand held delivery system
C_LIO_LIMechanical tests showed our transparent bio-adhesive has a higher adhesiveness compared to existing treatments and burst pressure threshold approximately 6.4 times higher than normal intraocular pressure.
C_LIO_LIIn vivo rabbit trial showed that compared to cyanoacrylate glue, the bio-adhesive was safer, faster healing and led to less pain in rabbits.
C_LI 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. Rapid evolution of seed dormancy during sunflower de-domestication Hybridization between crops and their wild relatives may promote the evolution of de-domesticated (feral) weeds. Wild sunflower (Helianthus annuus L.) is typically found in ruderal environments, but crop-wild hybridization may facilitate the evolution of weedy populations. Using one crop-specific mitochondrial marker (CMS-PET1) and 14 nuclear SSR markers, we studied the origin and genetic diversity of a recently discovered weedy population of sunflower (named BRW). Then, using a resurrection approach, we tested for rapid evolution of weedy traits (seed dormancy, herbicide resistance, and competitive ability) by sampling weedy and wild populations 10 years apart (2007 and 2017). All the weedy plants present the CMS-PET1 cytotype, confirming their feral origin. At the nuclear markers, BRW showed higher genetic diversity than the cultivated lines and low differentiation with one wild population, suggesting that wild hybridization increased their genetic diversity. We found support for rapid evolution towards higher seed dormancy, but not for higher competitive ability or herbicide resistance. Our results highlight the importance of seed dormancy during the earliest stages of adaptation and show that crop-wild hybrids can evolve quickly in agricultural environments. D1- and D2-like Receptors Differentially Mediate the Effects of Dopaminergic Transmission on Cost/Benefit Evaluation and Motivation in Monkeys It has been widely accepted that dopamine (DA) plays a major role in motivation, yet the specific contribution of DA signaling at D1-like receptor (D1R) and D2-like receptor (D2R) to cost-benefit trade-off remains unclear. Here, by combining pharmacological manipulation of DA receptors (DARs) and positron emission tomography imaging, we assessed the relationship between the degree of D1R/D2R blockade and changes in benefit- and cost-based motivation for goal-directed behavior of macaque monkeys. We found that the degree of blockade of either D1R or D2R was associated with a reduction of the positive impact of reward amount and increasing delay-discounting. Workload-discounting was selectively increased by D2R antagonism. In addition, blocking both D1R and D2R had a synergistic effect on delay-discounting but an antagonist effect on workload-discounting. These results provide fundamental in-sight into the distinct mechanisms of DA action in the regulation of the cost and benefit-based motivation, which have important implications for motivational alterations in both neurological and psychiatric disorders. Growth and division mode plasticity is dependent on cell density in marine-derived black yeasts The diversity and ecological contribution of the fungus kingdom in the marine environment remain under-studied. A recent survey in the Atlantic (Woods Hole, MA, USA) brought to light the diversity and unique biological features of marine fungi. The study revealed that black yeast species undergo an unconventional cell division cycle, which has not been documented in conventional model yeast species such as Saccharomyces cerevisiae (budding yeast) and Schizosaccharomyces pombe (fission yeast). The prevalence of this unusual property is unknown. Here, I collected and identified 65 marine fungi species across 40 genera from the surface ocean water, sediment, and the surface of macroalgae (seaweeds) in the Pacific (Sugashima, Toba, Japan). The Sugashima collection largely did not overlap with the Woods Hole collection and included several unidentifiable species, further illustrating the diversity of marine fungi. Three black yeast species were isolated, two of which were commonly found in Woods Hole (Aureobasidium pullulans, Hortaea werneckii). Surprisingly, their cell division mode was dependent on cell density, and the previously reported unconventional division mode was reproduced only at a certain cell density. For all three black yeast species, cells underwent filamentous growth with septations at low cell density and immediately formed buds at high cell density. At intermediate cell density, two black yeasts (H. werneckii and an unidentifiable species) showed rod cells undergoing septation at the cell equator. In contrast, all eight budding yeast species showed a consistent division pattern regardless of cell density. This study suggests the plastic nature of the growth/division mode of marine-derived black yeast. Towards a unified model of naive T cell dynamics across the lifespan Naive CD4 and CD8 T cells are cornerstones of adaptive immunity, but the dynamics of their establishment early in life and how their kinetics change as they mature following release from the thymus are poorly understood. Further, due to the diverse signals implicated in naive T cell survival, it has been a long-held and conceptually attractive view that they are sustained by active homeostatic control as thymic activity wanes. Here we employ multiple experimental systems to identify a unified model of naive CD4 and CD8 T cell population dynamics across the mouse lifespan. We infer that both subsets divide rarely and progressively increase their survival capacity with cell age. Strikingly, this simple model captures naive CD4 T cell dynamics throughout life. In contrast, we find that newly generated naive CD8 T cells are lost more rapidly during the first 3-4 weeks of life, likely due to increased recruitment into memory. We find no evidence for elevated division rates in neonates, or for feedback regulation of naive T cell numbers at any age. We show how confronting mathematical models with diverse datasets can reveal a quantitative and remarkably simple picture of naive T cell dynamics from birth into old age. Genomic databanks and targeted assays help characterise domestic mosquito incursions Biosecurity strategies aiming to restrict the spread of invasive pests can benefit from knowing where new incursions have come from. This knowledge can be acquired using genomic databanks, where genetic variation in incursion samples is compared against variation in reference samples. Here, we use genomic databanks to investigate domestic incursions of two mosquito species in Australia. We used a deep learning method to trace a 2021 invasion of Aedes aegypti in Tennant Creek, Northern Territory, to Townsville, Queensland, and to trace Ae. albopictus incursions between several invaded and uninvaded islands in the Torres Strait. We observed high precision of tracing despite 30-70 generations separating incursions and source samples. Targeted assays also improved precision, in this case by comparing Wolbachia infection data to mitochondrial DNA variation in Ae. aegypti. For Ae. albopictus, incursions detected in 2021 were traced to different islands than incursions detected in 2019. Patterns of relatedness and inbreeding indicated that Tennant Creek was likely invaded by Ae. aegypti from one family, whereas Torres Strait incursions involved distinct kinship groups. Our results highlight the value of repeated tracing with genomic databanks that remain informative over years, and demonstrate how additional targeted assays (e.g. Wolbachia) can improve inferences. Behavioural analysis of swarming mosquitoes reveals higher hearing sensitivity than previously measured with electrophysiology methods Mosquitoes of many species mate in station-keeping swarms. Mating chases ensue as soon as a male detects the flight tones of a female with his auditory organs. Previous studies of hearing thresholds have mainly used electrophysiological methods that prevent the mosquito from flying naturally. The main aim of this study was to quantify behaviourally the sound-level threshold at which males can hear females. Free-flying male Anopheles coluzzii were released in a large arena (~2 m high x 2 m x 1 m) with a conspicuous object on the ground that stimulates swarming behaviour. Males were exposed to a range of natural and synthetic played-back sounds of female flight. We monitored the responses of males and their distance to the speaker by recording changes in their wingbeat frequency and angular speed. We show that the mean male behavioural threshold of particle-velocity hearing lies between 13-20 dB SVL (95%-CI). A conservative estimate of 20 dB SVL (i.e., < 0.5 m/s particle velocity) is already 12 to 26 dB lower than most of the published electrophysiological measurements from the Johnstons organ. In addition, we suggest that 1) the first harmonic of female flight-sound is sufficient for males to detect her presence, 2) males respond with a greater amplitude to single-female sounds than to the sound of a group of females and 3) the response of males to the playback of the flight sound of a live female is the same as that of a recorded sound of constant frequency and amplitude. An Evolutionary Process Without Variation and Selection Natural selection successfully explains how organisms accumulate adaptive change despite that traits acquired over a lifetime are eliminated at the end of each generation. However, in some domains that exhibit cumulative, adaptive change--e.g., cultural evolution, and earliest life--acquired traits are retained; these domains do not face the problem that Darwins theory was designed to solve. Lack of transmission of acquired traits occurs when germ cells are protected from environmental change, due to a self-assembly code used in two distinct ways: (i) actively interpreted during development to generate a soma, and (ii) passively copied without interpretation during reproduction to generate germ cells. Early life and cultural evolution appear not to involve a self-assembly code used in these two ways. We suggest that cumulative, adaptive change in these domains is due to a lower-fidelity evolutionary process, and model it using Reflexively Autocatalytic and Foodset-generated networks. We refer to this more primitive evolutionary process as Self-Other Reorganisation (SOR) because it involves internal self-organising and self-maintaining processes within entities, as well as interaction between entities. SOR encompasses learning but in general operates across groups. We discuss the relationship between SOR and Lamarckism, and illustrate a special case of SOR without variation. Where there's smoke, there's fuel: dynamic vegetation data improve predictions of wildfire hazard in the Great Basin Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, non-forested ecosystems is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32 yr time series of spatial data, we employed machine learning algorithms to predict the relative probability of large (>405 ha) wildfire in the Great Basin based on fine-scale annual and 16-day estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluated the predictive utility of these models with a leave-one-year-out cross-validation, building spatial hindcasts of fire probability for each year that we compared against actual footprints of large wildfires. Herbaceous aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of burning. Across 32 fire seasons, 88% of the area burned in large wildfires coincided with the upper 3 deciles of predicted fire probabilities. At the scale of the Great Basin, several metrics of fire activity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather-driven growth of fine fuels and reveal a significant increasing trend in fire probability over the last three decades driven by widespread changes in fine fuel characteristics.