Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative ‘omics’ approach for prediction of candidate Strongyloides stercoralis diagnostic coproantigens

Human infection with the intestinal nematode Strongyloides stercoralis is persistent unless effectively treated, and potentially fatal in immunosuppressed individuals. Epidemiological data are lacking due to inadequate diagnosis. A rapid antigen detection test is a priority for population surveillance, validating cure after treatment, and for screening prior to immunosuppression. We analysed open access ‘omics’ data sets and used online predictors to identify S. stercoralis proteins that are likely to be present in infected stool, Strongyloides-specific, and antigenic. Transcriptomic data from gut and non-gut dwelling life cycle stages of S. stercoralis revealed 328 proteins that are differentially expressed. Strongyloides ratti proteomic data for excreted and secreted (E/S) proteins were matched to S. stercoralis, giving 1,057 orthologues. Five parasitism-associated protein families (SCP/TAPS, prolyl oligopeptidase, transthyretin-like, aspartic peptidase, acetylcholinesterase) were compared phylogenetically between S. stercoralis and outgroups, and proteins with least homology to the outgroups were selected. Proteins that overlapped between the transcriptomic and proteomic datasets were analysed by multiple sequence alignment, epitope prediction and 3D structure modelling to reveal S. stercoralis candidate peptide/protein coproantigens. We describe 22 candidates from seven genes, across all five protein families for further investigation as potential S. stercoralis diagnostic coproantigens, identified using open access data and freely-available protein analysis tools. This powerful approach can be applied to many parasitic infections with ‘omic’ data to accelerate development of specific diagnostic assays for laboratory or point-of-care field application. Author summary The worm Strongyloides stercoralis causes infectious disease in people throughout tropical and sub-tropical regions, leading to an extensive reduction in quality of life and even death. Millions of people are at risk of infection with this parasite and improved diagnostic and control methods and technologies are urgently required. Currently, most diagnosis is carried out through methods involving visual inspection of patient’s faeces, which has a number of drawbacks, particularly its poor sensitivity. This paper presents a new method to develop improved diagnostic tests for S. stercoralis, by computational analysis of publicly available gene and protein sequences to predict proteins that may be detectable in faeces. This would enable the development of rapid diagnostic tests in the form of lateral flows or dipsticks, with better predictive ability and fewer drawbacks than current diagnostic methods. A number of potential proteins, predicted to have all the desired characteristics for use in such tests were found through the new method and have been presented in this paper. With validation, new diagnostic tests for S. stercoralis could be developed from these results and the computational approach could be used to target other parasitic diseases.
Protein engineering shows antifreeze activity scales with ice-binding site area

The ice-binding site (IBS) of the 9.6-kDa springtail (Collembola) antifreeze protein from Granisotoma rainieri was identified by mutagenesis. We then studied the protein’s activity as a function of IBS area. Its polyproline type II helical bundle fold facilitates changes to both IBS length and width. A one third increase in IBS width, through the addition of a single helix doubled antifreeze activity. A one third decrease in area reduced activity to 10%. A construct engineered with an additional tripeptide turn in each helix displayed a 5-fold decrease in activity. Molecular dynamics suggested that the lengthened IBS is more twisted than the wild type, emphasizing the importance of a flat surface for antifreeze activity.
Tailored machine learning models for functional RNA detection in genome-wide screens

The in silico prediction of non-coding and protein-coding genetic loci is an area of research that has gathered large attention in the field of comparative genomics. In the last decade, much effort has been made to investigate numerous properties of nucleotide sequences that hint at their biological role in the cell. We present here a software framework for the alignment-based training, evaluation and application of machine learning models with user-defined parameters. Instead of focusing on the one-size-fits-all approach of pervasive in silico annotation pipelines, we offer a framework for the structured generation and evaluation of models based on arbitrary features and input data, focusing on stable and explainable results. Furthermore, we showcase the usage of our software package in a full-genome screen of Drosophila melanogaster and evaluate our results against the well-known but much less flexible program RNAz.
Reorganizing Niche Architecture Still Preserves Organ Function in the Hair Follicle

Stem cells’ ability to build and replenish tissues depends on support from their niche. While niche architecture varies across different organs, the functional importance of niche architecture is unclear. During hair follicle growth, multipotent epithelial progenitors build hair via crosstalk with their remodeling fibroblast niche, the dermal papilla, providing a powerful model to functionally interrogate different niche architectures. Through intravital imaging, we show that dermal papilla fibroblasts remodel both individually and collectively to form a polarized, structurally robust niche. Polarized TGFβ signaling precedes structural niche polarity, and loss of TGFβ signaling in dermal papilla fibroblasts leads them to progressively lose their stereotypic architecture and instead surround the epithelium. The reorganized niche relocates multipotent progenitors, but nevertheless supports their proliferation and differentiation. However, progenitor differentiation is completed prematurely, resulting in compromised hair production. Overall, our results reveal that niche architecture optimizes organ efficiency, but is not absolutely essential for organ function.
Evaluating microbial contaminations of alternative heating oils

Since 2008, legislative initiatives for climate protection and reduced dependency on fossil resource imports led to the introduction of biofuels as CO2-reduced alternatives in the heating oil sector. In the case of biodiesel, the oil industry or its customers were confronted with accelerated and escalating microbial contaminations during heating oil storage. Since then, other fuel alternatives, like hydrogenated vegetable oils, gas-to-liquid products (GtL), or Oxymethylenether (OME) have been or will be developed and potentially introduced to the market. In this study, we use online monitoring of microbial CO2 production and the simulation of onset of microbial contamination to investigate the contamination potential of fuel alternatives during storage. As reference and blends, fossil heating oils of various refineries, in the course of this from various crude oils, and refinery processes reveal considerable variation in potential microbial activity. Oxymethylene ethers have an antimicrobial effect, while various forms of biodiesel confirm the promotion of microbial activity and diversity. The paraffinic Fischer-Tropsch products and biogenic hydrogenation products demonstrate high resistance to microbial contamination despite allowing microbial diversity. Through an array of analytics, including advanced chromatography coupled mass spectrometry, elemental analysis, and microbial sequencing, we can discuss critical fuel properties that promote or inhibit microbial contaminations. In summary, novel, non-fossil heating oils show different strengths and weaknesses for long-term storage. Designing blends for microbial activity reduced long-term storage might be an option. While being niche products, these fuels will contribute to the rapid reduction of fossil resource use.
CIDP: a multi-functional platform for designing CRISPR sgRNAs

Most of sgRNA-design tools can be run under the precondition of the choice of closely-related species. However, it is hard to select an ideal closely-related species, as more and more different species were studied, and this situation was particular seriously in plant studies. Here, we introduced a new software, CRISPR Integrated Design Platform (CIDP), to solve the problem by allowing users to input genomic sequences for designing sgRNAs. The main function of CIDP was to design sgRNAs after building the sgRNA database using the input genomic sequences. Furthermore, in order to minimize the off-target effects, CIDP will search sgRNAs that appear only once across the whole genome on the target sequences. Meanwhile, CIDP set relevant functions to identify shared sgRNAs of a group of genes. Moreover, we also set primer design and sequence extraction functions in CIDP to help users design sgRNAs efficiently.
Salinomycin disturbs Golgi apparatus function and specifically affects cells in epithelial-to-mesenchymal transition

Epithelial-to-mesenchymal transition (EMT) gives rise to cells with properties similar to cancer stem cells (CSCs). Targeting the EMT program to selectively eliminate CSCs is a promising way to improve cancer therapy. Salinomycin (Sal), a K+/H+ ionophore, was identified as highly selective towards CSC-like cells, but its mechanism of action and selectivity remains elusive. Here we show that Sal, similarly to monensin and nigericin, disturbs the function of the Golgi apparatus (GA). Sal alters the expression of GA-related genes and leads to marked changes in GA morphology, particularly in cells that underwent EMT. Moreover, GA disturbing agents severely affect protein post-translational modifications including protein processing, glycosylation and secretion. We discover that the alterations induced by GA disturbing agents specifically affect the viability of EMT cells. Collectively, our work identifies a new vulnerability related to the EMT, suggesting that targeting the GA is a novel therapeutic approach against CSCs.
The Use of RF Waves in Space Propulsion Systems

This paper will review the ways in which RF and microwave radiation may be used in the design of electric propulsion systems for spacecraft. RF power has been used or proposed in electric propulsion systems to ionize, to heat, and to accelerate the propellant, or to produce plasma used to inflate a magnetic field for solar sail purposes. Direct RF propulsion using radiation pressure or ponderomotive forces is impractical owing to efficiency considerations. Examples of various systems that have been developed or proposed will be reviewed. The Variable Specific Impulse Magnetoplasma Rocket (VASIMR) uses RF for producing, heating and accelerating plasma. Inductive RF and microwave ion thruster schemes use e-m waves to ionize the plasma, which is then accelerated by use of dc grids. The details of the VASIMR, an inductive RF thruster, and a microwave ion thruster are discussed and contrasted with related RF systems.
Sleep spindle maturation enhances slow oscillation-spindle coupling

The synchronization of canonical fast sleep spindle activity (12.5-16 Hz) precisely during the slow oscillation up peak is considered an essential feature of adult non-rapid eye movement sleep. However, there is little knowledge on how this well-known coalescence between slow oscillations and sleep spindles develops. Leveraging individualized detection of single events, we first provide a detailed cross-sectional characterization of age-specific patterns of slow and fast sleep spindles, slow oscillations, and their coupling in children aged 5 to 6, 8 to 11, and 14 to 18 years. Critically, based on this, we then investigated how spindle and slow oscillation maturity substantiate age differences in their precise orchestration. While the predominant type of fast spindles was development-specific in that it was still nested in a frequency range below the canonical fast spindle range for the majority of children, the well-known slow oscillation-spindle coupling pattern was evident for sleep spindles in the canonical (adult-like) fast spindle range in all three age groups – but notably less precise in children. To corroborate these findings, we linked personalized measures of fast spindle maturity, which indicate the similarity between the prevailing development-specific and adult-like fast spindles, and slow oscillation maturity, which reflects the extent to which slow oscillations show frontal dominance, with individual slow oscillation-spindle coupling patterns. Importantly, we found that fast spindle maturity was uniquely associated with enhanced slow oscillation-spindle coupling strength and precision. Taken together, our results suggest that the increasing ability to generate canonical fast sleep spindles actuates precise slow oscillation-spindle coupling patterns across child and adolescent development.
Imaging through Windansee electrode arrays reveals a small fraction of local neurons following surface MUA

Prior studies have shown that neuronal spikes can be recorded with microelectrode arrays placed on the cortical surface. However, the etiology of these spikes remains unclear. Because the top cortical layer (layer 1) contains very few neuronal cell bodies, it has been proposed that these spikes originate from neurons with cell bodies in layer 2. To address this question, we combined two-photon calcium imaging with electrophysiological recordings from the cortical surface in awake mice using chronically implanted PEDOT:PSS electrode arrays on transparent parylene C substrate. Our electrode arrays (termed Windansee) were integrated with cortical windows offering see-through optical access while also providing measurements of local field potentials (LFP) and multiunit activity (MUA) from the cortical surface. To enable longitudinal data acquisition, we have developed a mechanical solution for installation, connectorization, and protection of Windansee devices aiming for an unhindered access for high numerical aperture microscope objectives and a lifetime of several months while worn by a mouse. Contrary to the common notion, our measurements revealed that only a small fraction of layer 2 neurons from the sampled pool (~13%) faithfully followed MUA recorded from the surface above the imaging field-of-view. Surprised by this result, we turned to computational modeling for an alternative explanation of the MUA signal. Using realistic modeling of neurons with back-propagating dendritic properties, we computed the extracellular action potential at the cortical surface due to firing of local cortical neurons and compared the result to that due to axonal inputs to layer 1. Assuming the literature values for the cell/axon density and firing rates, our modeling results show that surface MUA due to axonal inputs is over an order of magnitude larger than that due to firing of layer 2 pyramidal neurons. Thus, a combination of surface MUA recordings with two-photon calcium imaging can provide complementary information about the input to a cortical column and the local circuit response. Cortical layer I plays an important role in integration of a broad range of cortico-cortical, thalamocortical and neuromodulatory inputs. Therefore, detecting their activity as MUA while combining electrode recording with two-photon imaging using optically transparent surface electrode arrays would facilitate studies of the input/output relationship in cortical circuits, inform computational circuit models, and improve the accuracy of the next generation brain-machine interfaces.
CRF neurons establish resilience via stress-history dependent BNST modulation

Cumulative stress is a major risk factor for developing major depressive disorder (MDD), yet not everyone experiencing chronic stress develops MDD. In those who do not, it is unclear at what point, or by what mechanism, a trajectory of stable resiliency emerges. Utilizing a 10-day repeated social defeat stress model (RSDS) for MDD, we observed that a critical period between 7 and 10 daily defeats marks the phenotypical divergence of resilient from susceptible mice. In response to ongoing stress, corticotropin-releasing factor (CRF) neurons of the oval nucleus of the bed nucleus of the stria terminalis (BNSTov) display a sustained increased firing rate in resilient, but not susceptible mice. This neurophysiological adaptation was self-sustaining, but only after 7 critical stress exposures, indicating that the process of developing resilience is dependent on stress history. Our study reveals a novel process by which individuals might persist in the face of adversity by way of stress-provoked activation, not inhibition of a key CRF limbic region that establishes a pathway to resilience.
Single-molecule identification of the target RNAs of different RNA binding proteins simultaneously in cells

RNA-binding proteins (RBPs) regulate nearly every aspect of mRNA processing and are important regulators of gene expression in cells. However, current methods for transcriptome-wide identification of RBP targets are limited since they examine only a single RBP at a time and since they do not provide information on the individual RNA molecules that are bound by a given RBP. Here, we overcome these limitations by developing TRIBE-STAMP, an approach for single-molecule detection of the target RNAs of two RNA binding proteins simultaneously in cells. We apply TRIBE-STAMP to the cytoplasmic m6A reader proteins YTHDF1, 2, and 3 and discover that individual mRNA molecules can be bound by more than one YTHDF protein throughout their lifetime, providing new insights into the function of YTHDF proteins in cells. TRIBE-STAMP is a highly versatile approach that enables single-molecule analysis of the targets of RBP pairs simultaneously in the same cells.
Atg1 and Marf collaborate to maintain germline stem cells in Drosophila

Mitochondrial dynamics (fusion and fission) has been demonstrated to necessary for stem cell maintenance and differentiation, however, the relation between mitophagy, mitochondrial dynamics and stem cell exhaustion is not clearly understood. Here we report the multifaceted role of Atg1 in mitophagy, mitochondrial dynamics and stem cell maintenance in female germline stem cells (GSCs) in Drosophila . We found that depletion of Atg1 in GSCs leads to impaired autophagy (mitophagy) as measured by reduced formation of autophagosomes, increased accumulation of p62/Ref(2)P and accumulation of damaged mitochondria. We observed increased generation of mitochondrial reactive oxygen species (mROS) in GSCs with depleted Atg1 and mitochondrial clustering/fusion in cysts with Atg1 knockdown (Atg1KD). The mitochondrial clustering/fusion observed in Atg1KD cysts was due to increase in Marf levels and the mitochondrial phenotype could be rescued by overexpression of Drp1 or by depleting Marf via RNAi in Atg1KD cyst cells. Interestingly, double knockdown of both Atg1:Drp1 and Atg1:Marf affected ovariole size, number of GCs and the number of vitellogenic oocytes. Strikingly, Atg1:Marf double knockdown leads to loss of GSCs, differentiated GCs and a total loss of vitellogenic stages suggesting block in oogenesis. Overall, our results demonstrate that Drp1, Marf and Atg1 function together to influence female germline stem cell maintenance and differentiation of cystoblasts into cysts. we demonstrate the importance of Atg1 in of basal and its role in using RNAi and loss of function clones of Atg1 . Atg1 knockdown cyst cells also show a different mitochondrial implies a relation between the mitophagy machinery and the mitochondrial fission and fusion proteins. Using a combination of genetics and cell biology we demonstrate that Drp1, Marf and Atg1 collaborate to regulate stem cell maintenance in Drosophila. suggest that Drp1, Marf and Atg1 function together to regulate both maintenance and differentiation of GSCs during Drosophila oogenesis.
Modelling perception as a hierarchical competition differentiates imagined, veridical, and hallucinated percepts

Mental imagery is a process by which thoughts become experienced with sensory characteristics. Yet, it is not clear why mental images appear diminished compared to veridical images, nor how mental images are phenomenologically distinct from hallucinations, another type of non-veridical sensory experience. Current evidence suggests that imagination and veridical perception share neural resources. If so, we argue that considering how neural representations of externally-generated stimuli (i.e. sensory input) and internally-generated stimuli (i.e. thoughts) might interfere with one another can sufficiently differentiate veridical, imaginary, and hallucinatory perception. We here use a simple computational model of a serially-connected, hierarchical network with bidirectional information flow to emulate the primate visual system. We show that modelling even first-approximations of neural competition can more coherently explain imagery phenomenology than non-competitive models. Our simulations predict that, without competing sensory input, imagined stimuli should ubiquitously dominate hierarchical representations. However, with competition, imagination should dominate high-level representations but largely fail to outcompete sensory inputs at lower processing levels. To interpret our findings, we assume low-level stimulus information (e.g. in early visual cortex) contributes most to the sensory aspects of perceptual experience, while high-level stimulus information (e.g. towards temporal regions) contributes most to its abstract aspects. Our findings therefore suggest that ongoing bottom-up inputs during waking life may prevent imagination from overriding veridical sensory experience. In contrast, internally-generated stimuli may be hallucinated when sensory input is dampened or eradicated. Our approach can explain individual differences in imagery, along with aspects of daydreaming, hallucinations, and non-visual mental imagery.
Identification of Biomarker Genes Based on Multi-Omics Analysis in Non-Small Cell Lung Cancer

Background Non-small cell lung cancer (NSCLC) is a complex disease with a high mortality rate and a poor prognosis, but its molecular mechanisms and effective biomarkers are still unclear. Comprehensive analysis of multiple histological data can effectively exclude random events and is helpful in improving the reliability of the findings. In this study, we used three types of omics data, RNA-seq, microRNA-seq, and DNA methylation data, from public databases to explore the potential biomarker genes of two major subtypes of NSCLC. Results Through the combined differential analysis of multi-omics, we found 873 and 1378 potential high-risk genes in LUAD and LUSC, respectively. Then, we used WGCNA and PPI analyses to identify hub-genes and LASSO regression to construct prognostic models, and we obtained 15 prognostic genes. We also used survival analysis, univariate COX analysis, and GEO datasets to validate prognostic genes. Finally, we found ten genes associated with NSCLC, and eight of them have been reported in previous research. Conclusions In this study, two novel biomarker genes were identified: NES and ESAM. The two genes were both gene expression down-regulation and DNA methylation up-regulation, and regulated by miR-122 and miR-154. Moreover, the NES gene can contribute to the clinical diagnosis and prognosis of NSCLC.