Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent development of micro-triangulation for magnet fiducialisation

The micro-triangulation method is proposed as an alternative for magnet fiducialisation. The main objective is to measure horizontal and vertical angles to fiducial points and stretched wires, utilising theodolites equipped with cameras. This study aims to develop various methods, algorithms and software tools to enable the data acquisition and processing. In this paper, we present the first test measurement as an attempt to demonstrate the feasibility of the method and to evaluate the accuracy. The preliminary results are very promising, with accuracy always better than 20 μm for the wire position, and of about 40 μm/m for the wire orientation, compared with a coordinate measuring machine.
Plasma Amylin Immunoreactivity and Insulin Resistance in Insulin Resistant Relatives of Patients with Non-Insulin-Dependent Diabetes Mellitus

To explore the potential relationship between concentrations of circulating amylin and the insulin resistance observed in first-degree relatives of patients with non-insulin-dependent-diabetes mellitus (NIDDM), we studied 40 relatives compared to 35 matched controls. Two newly developed immunoassays that measure either non-glycosylated or total amylin were applied. All subjects were examined by an oral glucose tolerance test (OGTT) and by a hyperinsulinemic euglycemic clamp (insulin infusion: 0.6 mU/kg/mm). Glucose tolerance was normal in all, but insulin-stimulated glucose uptake (Rd) was diminished in the relatives (p <0.001). Area under the curves (AUCs) during OGTT for plasma glucose (p <0.01) and serum insulin (p 0.08), but not for plasma total and non-glycosylated amylin, were higher in relatives versus controls. In both groups, inverse correlations were found between Rd and AUC for plasma total and non-glycosylated amylin (p [all] <0.05). However, in multiple linear regression analyses, plasma total and non-glycosylated amylin failed to influence Rd independent of serum insulin and family history'of NIDDM. In conclusion, this study demonstrated inverse correlations between Rd and circulating concentrations of plasma total and non-glycosylated amylin in relatives and matched controls. These data, however, do not support the hypothesis that physiological amylin concentration are a major importance for the insulin resistance in relatives of NIDDM patients.
Actionable knowledge and creative projects: antecedents, practices, and outcomes

ABSTRACT The purpose of this study is to investigate actionable knowledge in the context of creative projects. A participant inductive investigation that relies primarily on observations and individual interviews was employed. This study identifies two antecedents and three distinct, though complementary, actionable knowledge-related practices of narrowing, broadening, and echoing. These are proposed so as to assist in the development of creative project outcomes and in sustaining an agentic workspace that contributes to collective learning and equalisation of outcomes. The findings of this study enrich the current literature on actionable knowledge in the context of creative projects.
METTL3 drives telomere targeting of TERRA lncRNA through m6A-dependent R-loop formation: a therapeutic target for ALT-positive neuroblastoma

Telomerase-negative tumors maintain telomere length by alternative lengthening of telomeres (ALT), but the underlying mechanism behind ALT remains poorly understood. A proportion of aggressive neuroblastoma (NB), particularly relapsed tumors, are positive for ALT (ALT+), suggesting that a better dissection of the ALT mechanism could lead to novel therapeutic opportunities. TERRA, a long non-coding RNA (lncRNA) derived from telomere ends, localizes to telomeres in a R-loop-dependent manner and plays a crucial role in telomere maintenance. Here we present evidence that RNA modification at the N6 position of internal adenosine (m6A) in TERRA by the methyltransferase METTL3 is essential for telomere maintenance in ALT+ cells, and the loss of TERRA m6A/METTL3 results in telomere damage. We observed that m6A modification is abundant in R-loop enriched TERRA, and the m6A-mediated recruitment of hnRNPA2B1 to TERRA is critical for R-loop formation. Our findings suggest that m6A drives telomere targeting of TERRA via R-loops, and this m6A-mediated R-loop formation could be a widespread mechanism employed by other chromatin-interacting lncRNAs. Furthermore, treatment of ALT+ NB cells with a METTL3 inhibitor resulted in compromised telomere targeting of TERRA and accumulation of DNA damage at telomeres, indicating that METTL3 inhibition may represent a therapeutic approach for ALT+ NB.
The Role of Agentive and Physical Forces in the Neural Representation of Motion Events

How does the brain represent information about motion events in relation to agentive and physical forces? In this study, we investigated the neural activity patterns associated with observing animated actions of agents (e.g., an agent hitting a chair) in comparison to similar movements of inanimate objects that were either shaped solely by the physics of the scene (e.g., gravity causing an object to fall down a hill and hit a chair) or initiated by agents (e.g., a visible agent causing an object to hit a chair). Using an fMRI-based multivariate pattern analysis (MVPA), this design allowed testing where in the brain the neural activity patterns associated with motion events change as a function of, or are invariant to, agentive versus physical forces behind them. A total of 29 human participants (nine male) participated in the study. Cross-decoding revealed a shared neural representation of animate and inanimate motion events that is invariant to agentive or physical forces in regions spanning frontoparietal and posterior temporal cortices. In contrast, the right lateral occipitotemporal cortex showed a higher sensitivity to agentive events, while the left dorsal premotor cortex was more sensitive to information about inanimate object events that were solely shaped by the physics of the scene.
tUbe net: a generalisable deep learning tool for 3D vessel segmentation

Deep learning has become an invaluable tool for bioimage analysis but, while open-source cell annotation software such as cellpose are widely used, an equivalent tool for three-dimensional (3D) vascular annotation does not exist. With the vascular system being directly impacted by a broad range of diseases, there is significant medical interest in quantitative analysis for vascular imaging. However, existing deep learning approaches for this task are specialised to particular tissue types or imaging modalities. We present a new deep learning model for segmentation of vasculature that is generalisable across tissues, modalities, scales and pathologies. To create a generalisable model, a 3D convolutional neural network was trained using data from multiple modalities including optical imaging, computational tomography and photoacoustic imaging. Through this varied training set, the model was forced to learn common features of vessels cross-modality and scale. Following this, the general model was fine-tuned to different applications with a minimal amount of manually labelled ground truth data. It was found that the general model could be specialised to segment new datasets, with a high degree of accuracy, using as little as 0.3% of the volume of that dataset for fine-tuning. As such, this model enables users to produce accurate segmentations of 3D vascular networks without the need to label large amounts of training data.
Characterization of the RofA regulon in the pandemic M1global and emergent M1UK lineages of Streptococcus pyogenes

Background & Aims The standalone regulator RofA is a positive regulator of the pilus locus in Streptococcus pyogenes. Found in only certain emm genotypes, RofA has been reported to regulate other virulence factors, although its role in the globally dominant emm1 S. pyogenes is unclear. Given the recent emergence of a new emm1 (M1UK) toxigenic lineage that is distinguished by three non-synonymous SNPs in rofA, we characterized the rofA regulon in six emm1 strains, that are representative of the two contemporary major emm1 lineages (M1global and M1UK) using RNAseq analysis, and then determined the specific role of the M1UK-specific rofA SNPs. Results Deletion of rofA in three M1global strains led to altered expression of 14 genes, including six non-pilus locus genes. In M1UK strains, deletion of rofA led to altered expression of 16 genes, including 9 genes that were unique to M1UK. Only the pilus locus genes were common to the RofA regulons of both lineages, while transcriptomic changes varied between strains even within the same lineage. Although introduction of the 3 SNPs into rofA did not impact gene expression in an M1global strain, reversal of 3 SNPs in an M1UK strain led to an unexpected number of transcriptomic changes that in part recapitulated transcriptomic changes seen when deleting RofA in the same strain. Computational analysis predicted interactions with a key histidine residue in the PRD domain of RofA would differ between M1UK and M1global. Summary RofA is a positive regulator of the pilus locus in all emm1 strains but effects on other genes are strain- and lineage-specific, with no clear, common DNA binding motif. The SNPs in rofA that characterize M1UK may impact regulation of RofA; whether they alter phosphorylation of the RofA PRD domain requires further investigation. Author summary RofA belongs to the group of “mga-like” bacterial regulatory proteins that comprise a DNA binding domain as well as a phosphorylation domain (PRD) that is responsive to changes in sugar availability. In certain emm genotypes of Streptococcus pyogenes, rofA sits upstream of the pilus locus, to act as a positive regulator. The recent emergence of a SpeA exotoxin-producing sublineage of emm1 S. pyogenes, (M1UK) has focused attention on the role of RofA; M1UK and its associated sublineages are characterized by 3 non-synonymous SNPs in rofA, that include adjacent SNPs in the PRD domain. Here, we determine the impact of rofA deletion and the 3 rofA SNPs in both the widely disseminated M1global clone and the newly emergent M1UK clone. While production of SpeA undoubtedly contributes to infection pathogenesis, the evolution of M1UK points to a role for metabolic regulatory rewiring in success of this lineage.
Growth directions and stiffness across cell layers determine whether tissues stay smooth or buckle

From smooth to buckled, nature exhibits organs of various shapes and forms. How cellular growth patterns produce smooth organ shapes like those of leaves and sepals remains unclear. Here we show that unidirectional growth and comparable stiffness across both epidermal layers of Arabidopsis sepals are essential for smoothness. We identified a mutant with ectopic ASYMMETRIC LEAVES 2 (AS2) expression that exhibits buckles on the outer epidermis due to conflicting growth directions and unequal epidermal stiffnesses. Aligning growth direction and increasing stiffness restores smoothness. Furthermore, buckling generates outgrowth by influencing auxin efflux transporter protein PIN-FORMED 1 polarity, indicating buckling can initiate organogenesis. Our findings suggest that in addition to molecular cues influencing tissue mechanics, tissue mechanics can also modulate molecular signals, giving rise to well-defined shapes. One-Sentence Summary The keys to unlocking sepal smoothness are unidirectional growth and even stiffness; misplace them, it’s time to buckle up!
MiniBAR/KIAA0355 is a dual Rac and Rab effector required for ciliogenesis

Cilia protrude from the cell surface and play critical roles in in-tracellular signaling, environmental sensing and development. Actin-dependent contractility and intracellular trafficking are both required for ciliogenesis, but little is known about how these processes are coordinated. Here, we identified a Rac1-and Rab35-binding protein with a truncated BAR domain that we named MiniBAR (aka KIAA0355/GARRE) which plays a key role in ciliogenesis. MiniBAR colocalizes with Rac1 and Rab35 at the plasma membrane and on intracellular vesicles traffick-ing to the ciliary base and exhibits remarkable fast pulses at the ciliary membrane. MiniBAR depletion leads to short cilia resulting from abnormal Rac-GTP/Rho-GTP levels, increased acto-myosin-II-dependent contractility together with defective trafficking of IFT88 and ARL13B into cilia. MiniBAR-depleted zebrafish embryos display dysfunctional short cilia and hall-marks of ciliopathies including left-right asymmetry defects. Thus, MiniBAR is a unique dual Rac and Rab effector that con-trols both actin cytoskeleton and membrane trafficking for cili-ogenesis.
Detection of viral infection in cell lines using ViralCellDetector

Cell lines are commonly used in research to study biology, including gene expression regulation, cancer progression, and drug responses. However, cross-contaminations with bacteria, mycoplasma, and viruses are common issues in cell line experiments. Detection of bacteria and mycoplasma infections in cell lines is relatively easy but identifying viral infections in cell lines is difficult. Currently, there are no established methods or tools available for detecting viral infections in cell lines. To address this challenge, we developed a tool called ViralCellDetector that detects viruses through mapping RNA-seq data to a library of virus genome. Using this tool, we observed that around 10% of experiments with the MCF7 cell line were likely infected with viruses. Furthermore, to facilitate the detection of samples with unknown sources of viral infection, we identified the differentially expressed genes involved in viral infection from two different cell lines and used these genes in a machine learning approach to classify infected samples based on the host response gene expression biomarkers. Our model reclassifies the infected and non-infected samples with an AUC of 0.91 and an accuracy of 0.93. Overall, our mapping- and marker-based approaches can detect viral infections in any cell line simply based on readily accessible RNA-seq data, allowing researchers to avoid the use of unintentionally infected cell lines in their studies.
Endocytic vesicles act as vehicles for glucose uptake in response to growth factor stimulation

Glycolysis is a fundamental cellular process, yet its regulatory mechanisms remain incompletely understood. Here, we show that a subset of glucose transporter 1 (GLUT1/SLC2A1) co-endocytoses with platelet-derived growth factor (PDGF) receptor (PDGFR) upon PDGF-stimulation. Furthermore, multiple glycolytic enzymes localize to these endocytosed PDGFR/GLUT1-containing vesicles adjacent to mitochondria. Contrary to current models, which emphasize the importance of glucose transporters on the cell surface, we find that PDGF-stimulated glucose uptake depends on receptor/transporter endocytosis. Our results suggest that growth factors generate glucose-loaded endocytic vesicles that deliver glucose to the glycolytic machinery in proximity to mitochondria, and argue for a new layer of regulation for glycolytic control governed by cellular membrane dynamics.
Neural network models for the evolution of associative learning

The ability to learn from past experience is an important adaptation, but how natural selection shapes learning is not well understood. Here, we investigate the evolution of associative learning (the association of stimuli with rewards) by a modelling approach that is based on the evolution of neural networks (NNs) underlying learning. Individuals employ their genetically encoded NN to solve a learning task with fitness consequences. NNs inducing more efficient learning have a selective advantage and spread in the population. We show that in a simple learning task, the evolved NNs, even those with very simple architecture, outperform well-studied associative learning rules, such as the Rescorla-Wagner rule. During their evolutionary trajectory, NNs often pass a transitional stage where they functionally resemble Rescorla-Wagner learning, but further evolution shapes them to approximate the theoretically optimal learning rule. Networks with a simple architecture evolve much faster and tend to outperform their more complex counterparts on a shorter-term perspective. Also, on a longer-term perspective network complexity is not a reliable indicator of evolved network performance. These conclusions change somewhat when the learning task is more challenging. Then the performance of many evolved networks is not better than that of the Rescorla-Wagner rule; only some of the more complex networks reach a performance level close to the optimal Bayesian learning rule. In conclusion, we show that the mechanisms underlying learning influence the outcome of evolution. A neural-network approach allows for more flexibility and a wider set of evolutionary outcomes than most analytical studies, while at the same time, it provides a relatively straightforward and intuitive framework to study the learning process.
Decoding Semantics from Dynamic Brain Activation Patterns: From Trials to Task in EEG/MEG Source Space

The temporal dynamics within the semantic brain network and its dependence on stimulus and task parameters are still not well understood. Here, we addressed this by decoding task as well as stimulus information from source-estimated EEG/MEG data. We presented the same visual word stimuli in a lexical decision (LD) and three semantic decision (SD) tasks. The meanings of the presented words varied across five semantic categories. Source space decoding was applied over time in five ROIs in the left hemisphere (Anterior and Posterior Temporal Lobe, Inferior Frontal Gyrus, Primary Visual Areas, and Angular Gyrus) and one in the right hemisphere (Anterior Temporal Lobe). Task decoding produced sustained significant effects in all ROIs from 50-100 ms, both when categorising tasks with different semantic demands (LD-SD) as well as for similar semantic tasks (SD-SD). In contrast, semantic word category could only be decoded in lATL, rATL, PTC and IFG, between 250-500 ms. Furthermore, we compared two approaches to source space decoding: Conventional ROI-by-ROI decoding and combined-ROI decoding with back-projected activation patterns. The former produced more reliable results for word-category decoding while the latter was more informative for task-decoding. This indicates that task effects are distributed across the whole semantic network while stimulus effects are more focal. Our results demonstrate that the semantic network is widely distributed but that bilateral anterior temporal lobes together with control regions are particularly relevant for the processing of semantic information. Significance Statement Most previous decoding analyses of EEG/MEG data have focussed on decoding performance over time in sensor space. Here for the first time we compared two approaches to source space decoding in order to reveal the spatio-temporal dynamics of both task and stimulus features in the semantic brain network. This revealed that even semantic tasks with similar task demands can be decoded across the network from early latencies, despite reliable differences in their evoked responses. Furthermore, stimulus features can be decoded in both tasks but only for a subset of ROIs and following the earliest task effects. These results inform current neuroscientific models of controlled semantic cognition.
Kita crispants for systematic image-based genetic screens of complex traits in zebrafish larvae

With thousands of loci identified by genome-wide association studies for complex traits, there is a need for in vivo model systems that can reliably and quickly infer the role of large numbers of candidate genes. CRISPR/Cas9-based functional screens in F0 zebrafish represent such a system. However, negative controls used so far – including scrambled guide RNAs (gRNAs), inactivated Cas9, and sham injections – do not elicit the same cellular and organismal responses as mutagenesis by CRISPR/Cas9, and may fuel biased conclusions. Here, we show that targeting kita facilitates efficient optical pre-screening for successful mutagenesis, higher quality imaging data, and efficient classification of cases and controls. We identified and tested two gRNAs that target kita with similarly high mutagenic efficiency and effects on pigmentation, and are free from off-target effects or major effects on cardiometabolic traits. We propose several approaches that will result in valid, unbiased conclusions.
LucFlow: A method to measure Luciferase reporter expression in single cells

Reporter assays, in which the expression of an inert protein is driven by gene regulatory elements such as promoters and enhancers, are a workhorse for investigating gene regulation. Techniques for measuring reporter gene expression vary from single-cell or single-molecule approaches having low throughput to bulk Luciferase assays that have high throughput. We developed a Luciferase Reporter Assay using Flow-Cytometry (LucFlow), which measures reporter expression in single cells immunostained for Luciferase. We optimized and tested LucFlow with a murine cell line that can be differentiated into neutrophils, into which promoter-reporter and enhancer-promoter-reporter constructs have been integrated in a site-specific manner. The single-cell measurements are comparable to bulk ones but we found that dead cells have no detectable Luciferase protein, so that bulk assays underestimate reporter expression. LucFlow is able to achieve a higher accuracy than bulk methods by excluding dead cells during flow cytometry. Prior to fixation and staining, the samples are spiked with stained cells that can be discriminated during flow cytometry and control for tube-to-tube variation in experimental conditions. Computing fold change relative to control cells allows LucFlow to achieve a high level of precision. LucFlow, therefore, enables the accurate and precise measurement of reporter expression in a high throughput manner.
Invasion of the stigma by the pollen tube or an oomycete pathogen: striking similarities and differences

The epidermis is the first barrier that protects organisms from surrounding stresses. Similar to the hyphae of filamentous pathogens that penetrate and invade the outer tissues of the host, the pollen germinates and grows a tube within epidermal cells of the stigma. Early responses of the epidermal layer are therefore decisive for the outcome of these two-cell interaction processes. Here, we aim at characterizing and comparing how the papillae of the stigma respond to intrusion attempts, either by hypha of the hemibiotrophic oomycete root pathogen, Phytophthora parasitica or by the pollen tube. We found that P. parasitica spores attach to the papillae and hyphae subsequently invade the entire pistil. Using transmission electron microscopy, we examined in detail the invasive growth characteristics of P. parasitica and found that the hypha passed through the stigmatic cell wall to grow in contact with the plasma membrane, contrary to the pollen tube that advanced engulfed within the two cell wall layers of the papilla. Further quantitative image analysis revealed that the pathogen and the pollen tube trigger reorganization of the endomembrane system (trans Golgi network, late endosome) and the actin cytoskeleton. Some of these remodeling processes are common to both invaders, while others appear to be more specific showing that the stigmatic cells trigger an appropriate response to the invading structure and somehow can recognize the invader that attempts to penetrate.