Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of repetitive DNA in re-patterning of major rDNA clusters in Lepidoptera

Genes for major ribosomal RNAs (rDNA) are present in multiple copies organized in tandem arrays. Number and position of rDNA loci can change dynamically and their re-patterning is presumably driven by repetitive sequences. We explored a peculiar rDNA organization in several representatives of Lepidoptera with either extremely large or numerous rDNA clusters. We combined molecular cytogenetics with analyses of second and third generation sequencing data to show that rDNA spreads as a transcription unit and reveal association between rDNA and various repeats. Furthermore, we performed comparative long read analyses between the species with derived rDNA distribution and moths with a single rDNA locus, which is considered ancestral. Our results suggest that satellite arrays, rather than mobile elements, facilitate homology-mediated spread of rDNA via either integration of extrachromosomal rDNA circles or ectopic recombination. The latter arguably better explains preferential spread of rDNA into terminal regions of lepidopteran chromosomes as efficiency of ectopic recombination depends on proximity of homologous sequences to telomeres.
Comparison of rule- and ordinary differential equation-based dynamic model of DARPP-32 signalling network

Dynamic modelling has considerably improved our understanding of complex molecular mechanisms. Ordinary differential equations (ODEs) are the most detailed and popular approach to modelling the dynamics of molecular systems. However, their application in signalling networks, characterised by multi-state molecular complexes, can be prohibitive. Contemporary modelling methods, such as rule-based (RB) modelling, have addressed these issues. The advantages of RB modelling over ODEs have been presented and discussed in numerous reviews. In this study, we conduct a direct comparison of the time courses of a molecular system founded on the same reaction network but encoded in the two frameworks. To make such a comparison, a set of reactions that underlie an ODE model was manually encoded in the Kappa language, one of the RB implementations. A comparison of the models was performed at the level of model specification and results were acquired through model simulations. Conforming to previous reports, we confirm that the Kappa model recapitulated the general dynamics of its ODE counterpart with minor differences. These differences occur whenever molecules have multiple sites binding the same interactor. Furthermore, activation of these molecules in the RB model is slower than in the ODE one but can be corrected by revision of the rate constants used in the relevant rules. As in previous reports on other molecular systems, we find that, also in the case of the DARPP-32 reaction network, the RB representation offers a more expressive and flexible syntax that facilitates access to fine details of the model, facilitating model reuse. In parallel with these analyses, this manuscript reports a refactored model of the DARPP-32 interaction network that can serve as a canvas for the development of a more complex interaction network to study this important molecular system.
circRAB3IP modulates cell proliferation by reorganizing gene expression and mRNA processing in a paracrine manner

Circular RNAs are endogenous long-lived and abundant non-coding species. Despite their prevalence, only few circRNAs have been dissected mechanistically to date. Here, we catalogued nascent RNA-enriched circRNAs from primary human cells and functionally assign a role to circRAB3IP in sustaining cellular homeostasis. We combined “omics” and functional experiments to show how circRAB3IP depletion deregulates hundreds of genes, suppresses cell cycle progression, and induces senescence-associated gene expression changes. Conversely, excess circRAB3IP delivered to endothelial cells via extracellular vesicles suffices for accelerating their division. We attribute these effects to the interplay between circRAB3IP and the general splicing factor SF3B1, which impacts transcript usage of cell cycle-related genes. Together, our findings link the maintenance of cell homeostasis to the tightly regulated titers of a single circRNA.
Transcriptome analysis reveals robust transcriptional reprogramming during early stages of Cicer-Ascochyta interaction

Ascochyta blight (AB) caused by a filamentous fungus Ascochyta rabiei is a major threat to global chickpea production. The mechanisms underlying chickpea response to A. rabiei remain elusive. Here, we investigated the comparative transcriptional dynamics of AB-resistant and susceptible chickpea genotypes upon A. rabiei infection to understand the early host defence response. Our findings revealed that AB-resistant plants underwent rapid and extensive transcriptional reprogramming compared to susceptible host. At early stage (24-hpi), mainly cell wall remodeling and secondary metabolite pathways were highly activated, while DEGs related with signaling components viz. protein kinases, transcription factors, and hormonal pathways show remarkable upsurge at 72-hpi, especially in resistant genotype. Notably, our data suggests imperative role of JA, ET, and ABA signaling in providing immunity against A. rabiei. Furthermore, gene co-expression networks and modules corroborated the importance of cell wall remodeling, signal transduction and phytohormone pathways. The hub genes such as MYB14, PRE6 and MADS-SOC1 discovered in these modules might be the master regulators governing chickpea immunity. Overall, we not only provide novel insights for comprehensive understanding of immune signaling components mediating AB resistance/susceptibility at early Cicer-Ascochyta interactions, but also offer a valuable resource for developing AB-resistant chickpea. Highlights Comparative transcriptomic and co-expression analysis of AB-resistant and susceptible chickpea genotypes reveals high-amplitude transcriptional dynamics in resistant plants, and also identifies TFs, PKs and phytohormone-crosstalk as core regulators for AB-resistance.
PIP4K2B is a mechanosensor and induces heterochromatin-driven nuclear softening through UHRF1

Phosphatidylinositol-5-phosphate (PtdIns5P)-4-kinases (PIP4Ks) are stress-regulated phosphoinositide kinases able to phosphorylate PtdIns5P to PtdIns(4, 5)P2. In cancer patients their expression is typically associated with bad prognosis. Among the three PIP4K isoforms expressed in mammalian cells, PIP4K2B is the one with more prominent nuclear localization. Here, we unveil the role for PIP4K2B as mechanosensor. PIP4K2B protein level, indeed, strongly decreases in cells growing on soft substrates. Its direct silencing or pharmacological inhibition, mimicking cell response to soft, triggers a concomitant reduction of the epigenetic regulator UHRF1 and induces changes in nuclear polarity, nuclear envelope tension and chromatin compaction. This substantial rewiring of the nucleus mechanical state drives YAP cytoplasmic retention and impairment of its activity as transcriptional regulator, finally leading to defects in cell spreading and motility. Since YAP signalling is essential for initiation and growth of human malignancies, our data suggest that potential therapeutic approaches targeting PIP4K2B could be beneficial in the control of the altered mechanical properties of cancer cells.
Indirect decoding of behavior from brain signals via reconstruction of experimental conditions

The data acquired during a functional magnetic resonance imaging (fMRI) experiment usually comprise experimental conditions, brain signals and behavioral responses. This reflects the underlying causal flow where the experimental conditions evoke brain responses that in turn result in behavior. In multivariate analyses, a common approach is to focus on the second step of that chain and to decode behavioral responses from brain signals. However, a different approach would be to first reconstruct the experimental conditions from brain signals and in turn use these to predict behavior. While this indirect approach would go against the causal chain of events, it might work better under certain circumstances, especially when the experimental conditions evoke much stronger measurable brain signals than the overt motor behavior. Here we tested this question directly by assessing the various mappings between conditions, brain signals and behavior in an open dataset. We found that the path of first decoding experimental conditions works surprisingly well, even though in our example data set, it is still outperformed by directly decoding the behavior from brain responses.
Establishing a reproducible approach for the controllable deposition and maintenance of plants cells with 3D bioprinting

Capturing cell-to-cell and cell-to-environment signals in a defined 3 dimensional (3D) microenvironment is key to study cellular functions, including cellular reprogramming towards tissue regeneration. A major challenge in current culturing methods is that these methods cannot accurately capture this multicellular 3D microenvironment. In this study, we established the framework of 3D bioprinting with plant cells to study cell viability, cell division, and cell identity. We established long-term cell viability for bioprinted Arabidopsis root cells and soybean meristematic cells. To analyze the large image datasets generated during these long-term viability studies, we developed an open source high-throughput image analysis pipeline. Furthermore, we showed the cell cycle re-entry of the isolated Arabidopsis and soybean cells leading to the formation of microcalli. Finally, we showed that the identity of isolated cells of Arabidopsis roots expressing endodermal markers maintained longer periods of time. The framework established in this study paves the way for a general use of 3D bioprinting for studying cellular reprogramming and cell cycle re-entry towards tissue regeneration.
Proton-transporting heliorhodopsins from marine giant viruses

Rhodopsins convert light into signals and energy in animals and microbes. Heliorhodopsins (HeRs), a recently discovered new rhodopsin family, are widely present in archaea, bacteria, unicellular eukaryotes, and giant viruses, but their function remains unknown. Here we report that a viral HeR from Emiliania huxleyi virus 202 (V2HeR3) is a light-gated proton channel. V2HeR3 absorbs blue-green lights, and the active intermediate contains the deprotonated retinal Schiff base. Site-directed mutagenesis study revealed that E191 in TM6 constitutes the gate together with the retinal Schiff base. E205 and E215 form a proton accepting group of the Schiff base, whose mutations converted the protein into an outward proton pump. Three environmental viral HeRs from the same group, as well as a more distantly related HeR exhibited similar proton-transport activity, indicating that HeR functions might be diverse similarly to type-1 microbial rhodopsins. Some strains of E. huxleyi contain one HeR that is related to the viral HeRs, while its viruses EhV-201 and EhV-202 contain two and three HeRs, respectively. Except for V2HeR3 from EhV-202, none of these proteins exhibit ion-transport activity. Thus, when expressed in the E. huxleyi cell membranes, only V2HeR3 has the potential to depolarize the host cells by light, possibly to overcome the host defense mechanisms or to prevent superinfection. The neuronal activity generated by V2HeR3 suggests that it can potentially be used as an optogenetic tools, like type-1 microbial rhodopsins.
Germline/soma distinction in Drosophila embryos requires regulators of zygotic genome activation

In Drosophila melanogaster embryos, somatic versus germline identity is the first cell fate decision. Zygotic genome activation (ZGA) orchestrates regionalized gene expression, imparting specific identity on somatic cells. ZGA begins with a minor wave that commences at nuclear cycle (NC) 8 under the guidance of chromatin accessibility factors (Zelda, CLAMP, GAF), followed by the major wave during NC14. By contrast, primordial germ cell (PGC) specification requires maternally deposited and posteriorly anchored germline determinants. This is accomplished by a centrosome coordinated release and sequestration of germ plasm during the precocious cellularization of PGCs in NC10. Here we report a novel requirement for Zelda and CLAMP during the establishment of the germline/soma distinction. When their activity is compromised, PGC determinants are not properly sequestered, and specification is disrupted. Conversely, the spreading of PGC determinants from the posterior pole adversely influences transcription in the neighboring somatic nuclei. These reciprocal aberrations can be correlated with defects in centrosome duplication/separation that are known to induce inappropriate transmission of the germ plasm. Interestingly, consistent with the ability of BMP signaling to influence specification of embryonic PGCs, reduction in the transcript levels of a BMP family ligand, decapentaplegic (dpp), is exacerbated at the posterior pole.
Complex developmental and transcriptional dynamics underlie pollinator-driven evolutionary transitions in nectar spur morphology in Aquilegia (columbine)

Premise Determining the developmental programs underlying morphological variation is key to elucidating the evolutionary processes that generated the stunning biodiversity of the angiosperms. Here, we characterize the developmental and transcriptional dynamics of the elaborate petal nectar spur of Aquilegia (columbine) in species with contrasting pollination syndromes and spur morphologies. Methods We collected petal epidermal cell number and length data across four Aquilegia species, two with the short, curved nectar spurs of the bee-pollination syndrome, and two with the long, straight spurs of the hummingbird syndrome. We also performed RNA-seq on A. brevistyla (bee) and A. canadensis (hummingbird) distal and proximal spur compartments at multiple developmental stages. Finally, we intersected these datasets with a previous QTL mapping study on spur length and shape to identify new candidate loci. Results The differential growth between the proximal and distal surfaces of curved spurs is primarily driven by differential cell division. However, independent transitions to straight spurs in the hummingbird syndrome have evolved by increasing differential cell elongation between spur surfaces. The RNA-seq data reveal these tissues to be transcriptionally distinct, and point to auxin signaling as being involved with the differential cell elongation responsible for the evolution of straight spurs. We identify several promising candidate genes for future study. Conclusions Our study, taken together with previous work in Aquilegia, reveals the complexity of the developmental mechanisms underlying trait variation in this system. The framework we have establish here will lead to exciting future work examining candidate genes and processes involved in the rapid radiation of the genus.
Robust estimation of 1/f activity improves oscillatory burst detection

Neural oscillations often occur as transient bursts with variable amplitude and frequency dynamics. Quantifying these effects is important for understanding brain-behaviour relationships, especially in continuous datasets. To robustly measure bursts, rhythmical periods of oscillatory activity must be separated from arrhythmical background 1/f activity, which is ubiquitous in electrophysiological recordings. The Better OSCillation (BOSC) framework achieves this by defining a power threshold above the estimated background 1/f activity, combined with a duration threshold. Here we introduce a modification to this approach called fBOSC which uses a spectral parametrisation tool to accurately model background 1/f activity in neural data. fBOSC (which is openly available as a MATLAB toolbox) is robust to power spectra with oscillatory peaks and can also model non-linear spectra. Through a series of simulations, we show that fBOSC more accurately models the 1/f power spectrum compared with existing methods. fBOSC was especially beneficial where power spectra contained a “knee” below ∼0.5-10 Hz, which is typical in neural data. We also found that, unlike other methods, fBOSC was unaffected by oscillatory peaks in the neural power spectrum. Moreover, by robustly modelling background 1/f activity, the sensitivity for detecting oscillatory bursts was standardised across frequencies (e.g. theta- and alpha-bands). Finally, using openly available resting state magnetoencephalography and intracranial electrophysiology datasets, we demonstrate the application of fBOSC for oscillatory burst detection in the theta-band. These simulations and empirical analyses highlight the value of fBOSC in detecting oscillatory bursts, including in datasets that are long and continuous with no distinct experimental trials. GRAPHICAL ABSRACT To determine a power threshold for burst detection, the Better OSCillation framework (BOSC) estimates background 1/f activity by modelling neural power spectra. Here we introduce a modification, termed fBOSC, to more robustly estimate 1/f activity in situations with prominent oscillatory peaks and/or the presence of a non-linear “knee” in the power spectrum. This was shown to standardise burst detection across frequency bands in both simulated and empirical data.
Ovipin: a new antimicrobial peptide from chicken eggs Gallus gallus

The intensive and indiscriminate use of antibiotic has increased cases of microorganisms resistance and becoming a worldwide public health problem. In the last years, from natural sources such as hen’s egg, have received special attention in the discovery of new bioactive compounds. This study aims to identify and characterize a new peptide from chicken egg of Gallus gallus domesticus. The chicken egg was subjected the extraction acid, the supernatant was prefractionated in Sep- Pak column and fractionated peptide by reverse-phase high-performance liquid chromatography (RP-HPLC). The antimicrobial activity of the fractions were evaluated through liquid growth inhibition assays. The molecular weight and amino acid sequence was determined by mass spectrometry (MS/MS), the characaterization performed by bioinformatics analysis with Peaks® tool and comparision with the NCBI and UniProt-SwisProt database. The physicochemical parameters of the samples were evaluated with online programs. One fraction named Ovipin peptide, showed antimicrobial activity against Gram-positive bacteria (Micrococcus luteus – MIC 1.94 µM) and Filamentous fungus (Aspergillus niger - MIC 31.01 µM). The minimum inhibitory concentration against Cryptococcus neoformans VNI (WM 148) Yeast was 15.51 µM, this microorganism an opportunistic yeast and mainly binds in immunosuppressed or immunocompromissed people. Ovipin is a hydrophoic peptide and not cause significant hemolytic effect against human erythrocytes. Ovipin primary sequence is YVSPVAIVKGLNIPL and a molecular weight of 1,581.94 Da. Ovipin shows 100% and 93.3%, respectively, sequence similarity with the fragments Apolipoprotein B of Gallus gallus and Apolipoprotein B of five others species of Aves. Our data suggest that Ovipin peptide could be a potential therapeutic candidate to be used an alternative against infections developed by resistant microorganisms, mainly in the fight against Cryptococcus neoformans opportunistic yeast.
Prediction Algorithm for Heat Demand of Science and Technology Topics Based on Time Convolution Network

Thanks to the rapid development of deep learning, big data analysis technology is not only widely used in the field of natural language processing, but also more mature in the field of numerical prediction. It is of great significance for the subject heat prediction and analysis of science and technology demand data. How to apply theme features to accurately predict the theme heat of science and technology demand is the core to solve this problem. In this paper, a prediction method of subject heat of science and technology demand based on time convolution network (TCN) is proposed to obtain the subject feature representation of science and technology demand. Time series prediction is carried out based on TCN network and self attention mechanism, which increases the accuracy of subject heat prediction of science and technology demand data Experiments show that the prediction accuracy of this algorithm is better than other time series prediction methods on the real science and technology demand datasets.
STRUCTURAL REALTIONSHIPS OF PASSENGER SATISFACTION WITH AIRLINE SERVICE QUALITY

This study aimed to examine the effects of aspects of airline service quality, such as airline/terminal tangibles and empathy on levels of customer satisfaction with service quality. The relationship between these levels of satisfaction and the general perceptions about service qualitywas also investigated.A total of 250 respondents who had regularly patronized either Malaysia Airlines orAirAsiaoverthe last six months were selected via convenience sampling method. Structural Equation Modeling (SEM) approach was used for data analysis. Empirical results via SEM revealed that the relationship between customer satisfaction with the service quality of the airline providers and „word-ofmouth‟ recommendations is a consistent one. Furthermore, customer satisfaction with the service quality of the airline providers is widely influenced by empathy, which is whyflightpunctuality and good transportation links between cityvenues and airports are prioritized by providers.
A comparative study of algorithms for generating switch cover test sets

Test case generation based on Finite State Machines (FSMs) has been extensively investigated due to its accuracy and simplicity. Several test criteria have been proposed in the literature to generate test cases based on FSMs. One of the oldest criteria is the Switch Cover. As a main feature, the Switch Cover criterion deﬁnes that all transition pairs of an FSM must be covered. The classical Switch Cover algorithm converts the FSM into a graph (known as Dual Graph); this graph is balanced, and, ﬁnally, traversed based on an Eulerian Cycle algorithm. In this context, considering the stage where an FSM is converted into a graph, this study investigates other search algorithms on graphs, namely Depth-First Search (DFS) and Breadth-First Search (BFS), for generating test sets from a Dual Graph. We presented an experimental study that compares the DFS, BFS algorithms with the Eulerian Cycle. The study was conducted with a set of random and real-world machines, taking into account the number of test cases, the test suite size, the average length of sequences and generation time.
Bidirectional Quasi-Cuk DC/DC Converter with Reduced Voltage Stress on Capacitor and Capability of Changing the Output Polarity

In this paper, a bidirectional topology for quasi-Cuk dc/dc converter with capability of zero-voltage and zero-current-switching (ZVZCS) is proposed. The bidirectional quasi-Cuk (BQ-Cuk) converter has different voltage and current transfer ratio, reduced voltage stress on capacitor and capability of changing the output polarity in comparison with conventional bidirectional Cuk converter. In this paper, steady-state analysis of the quasi-Cuk converter with capability of ZVZCS in turn-on is presented. Then, critical inductances for transient from this operation to two new operations are calculated. Next, besides values designing of used elements, maximum and minimum value of their current and voltage are calculated. Finally, experimental results to verify the accuracy of the proposed converter in different operating modes are presented.