Miracle-dz/UniFAR-FTUs huggingface dataset:
Jasmonic acid and methyl jasmonate attenuate neuroinflammation via crosstalk with the prostaglandin E2/receptor EP2 signaling axis

The jasmonates are a class of oxylipin phytohormones known to exhibit anti-inflammatory, antioxidant, and anti-cancer effects in mammalian cells. We investigated the ability of three jasmonate compounds (jasmonic acid, methyl jasmonate, and 12-OPDA) and two structurally distinct jasmonate precursors (alpha-linolenic acid and palmitic acid) to attenuate inflammation in an in vitro model of neurodegenerative disease, for which the mechanisms of action have not been well identified. The study modeled chronic neuroinflammation in SH-SY5Y neuroblastoma cells using exogenous prostaglandin E2 (PGE2) treatment. Prostaglandin E2 caused concentration-dependent levels of inflammation and SH-SY5Y cell death, which were attenuated by the jasmonates and their precursors. To this end, structural similarities between the jasmonates and PGE2 were correlated with increased potency of their anti-inflammatory effects. Downstream biomarkers of signaling through the pro-inflammatory E prostanoid receptor subtype 2 (EP2) were then quantified using enzyme-linked immunosorbent assay methods. Of the compounds tested, only jasmonic acid and methyl jasmonate attenuated inflammation in the SH-SY5Y cells via crosstalk with the PGE2/EP2 signaling axis. Additionally, structural models and molecular binding simulations serve as evidence for our hypothesis that JA and MeJA achieve this crosstalk through competitive inhibition of the receptor EP2. This novel finding has implications in the study of neurodegenerative diseases for which the disease pathology is related to chronic neuroinflammation, including Alzheimer’s Disease (AD), Parkinson’s Disease (PD), amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS). In addition, these findings add to the understanding of the relationship between pro-inflammatory prostaglandin E2 signaling and disease severity.
MetalPrognosis: a Biological Language Model-based Approach for Disease-Associated Mutations in Metal-Binding Site prediction

Protein-metal ion interactions play a central role in the onset of numerous diseases. When amino acid changes lead to missense mutations in metal-binding sites, the disrupted interaction with metal ions can compromise protein function, potentially causing severe human ailments. Identifying these disease-associated mutation sites within metal-binding regions is paramount for understanding protein function and fostering innovative drug development. While some computational methods aim to tackle this challenge, they often fall short in accuracy, commonly due to manual feature extraction and the absence of structural data. We introduce MetalPrognosis, an innovative, alignment-free solution that predicts disease-associated mutations within metal-binding sites of metalloproteins with heightened precision. Rather than relying on manual feature extraction, MetalPrognosis employs sliding window sequences as input, extracting deep semantic insights from pre-trained protein language models. These insights are then incorporated into a convolutional neural network, facilitating the derivation of intricate features. Comparative evaluations show MetalPrognosis outperforms leading methodologies like MCCNN and PolyPhen-2 across various metalloprotein test sets. Furthermore, an ablation study reiterates the effectiveness of our model architecture. To facilitate public use, we have made the datasets, source codes, and trained models for MetalPrognosis online available at http://metalprognosis.unimelb-biotools.cloud. edu.au/.
OPTIMISED SATELLITE COMMUNICATIONS USING WEATHER RADARS

This paper describes a novel method of continuous fade detection and level estimation using operational weather radars. The system is expected to allow accurate atmospheric attenuation detection and prediction throughout a very large area in the satellite footprints. The instantaneous attenuation information allows the centralized adaptation of the transmission parameters of all subsystems in a satellite network (hub, terminal, satellite). The use of attenuation distributions for satellite systems derived from weather radar measurements allows numerous ways of optimizing space communication applications, which are the subject of this paper
Gene surgery as a potential treatment option for Nephropathic Cystinosis in vitro

Nephropathic cystinosis is a rare monogenetic kidney disease caused by mutations in the lysosomal transporter cystinosin (encoded by CTNS) that, to date, has no cure. The hallmark of this disease is lysosomal accumulation of cystine and decline in proximal tubular function leading to kidney failure early in life. In this project, we developed a novel gene repair strategy using CRISPR/Cas9 Homology-Independent Targeted Integration (HITI) to restore CTNS. A novel, non-viral peptide-mediated approach was used to deliver the Cas9-guideRNA ribonucleoprotein (RNP) complex and repair templates to conditionally immortalized proximal tubule epithelial cell (ciPTEC) lines. The repair constructs contained either mCherry (1.7 kb), the CTNS Superexon (1.7 Kb) or both (3.2 Kb). The results demonstrated that the smaller mCherry construct achieved a higher repair efficiency (63%) compared to the CTNS-mCherry construct (16%). Clonal expansion of repaired cells showed restoration of lysosomal cystine levels in 70-75% of the clones, which was accompanied by improved mitochondrial bioenergetics. In conclusion, CRISPR/Cas9 HITI can be used to precisely insert repair templates into the genome, resulting in a functional cystinosin restoration, and a reversal of the cystinotic disease phenotype.
Ligand-Dependent Mechanisms of C-C Chemokine Receptor 5 (CCR5) Trafficking Revealed by APEX2 Proximity Labeling Proteomics

CC chemokine receptor 5 (CCR5) contributes to inflammatory responses by driving cell migration and scavenging chemokine to shape directional chemokine gradients. A drug against CCR5 has been approved for blocking HIV entry into cells. However, targeting CCR5 for the treatment of inflammatory diseases and cancer has had limited success because of the complex biology and pharmacology of this receptor. CCR5 is activated by many natural and engineered chemokines that elicit distinct receptor signaling and trafficking responses, including some that sequester the receptor inside the cell. The sequestration phenomenon may be therapeutically exploitable, but the mechanisms by which different ligands traffic CCR5 to different cellular locations are poorly understood. Here we employed live cell ascorbic acid peroxidase proximity labeling and quantitative mass spectrometry proteomics for unbiased discovery of temporally resolved protein neighborhoods of CCR5 following stimulation with its endogenous agonist, CCL5, and two CCL5 variants that promote intracellular retention of the receptor. Along with targeted pharmacological assays, the data reveals distinct ligand-dependent CCR5 trafficking patterns with temporal resolution. All three chemokines internalize CCR5 via β-arrestin- dependent, clathrin-mediated endocytosis but to different extents, with different kinetics and with varying dependencies on GPCR kinase subtypes. The agonists differ in their ability to target the receptor to lysosomes for degradation, as well as to the Golgi compartment and the trans-Golgi network, and these trafficking patterns translate into distinct levels of ligand scavenging. The results provide insight into the molecular mechanisms behind CCR5 intracellular sequestration and suggest actionable patterns for the development of chemokine-based CCR5 targeting molecules. Significance Statement CCR5 plays a crucial role in the immune system and is important in numerous physiological and pathological processes such as inflammation, cancer and HIV transmission. Along with its functional diversity, different CCR5 ligands can induce distinct receptor signaling responses and trafficking behaviors; the latter includes intracellular receptor sequestration which offers a potential therapeutic strategy for inhibiting CCR5 function. Using time-resolved proximity labeling proteomics and targeted pharmacological experiments, this study reveals the molecular basis for receptor sequestration including information that can be exploited for the development of CCR5 targeting molecules that promote retention of the receptor inside the cell.
Interior pycnocline flow from the subtropical to the Equatorial Pacific Ocean

Abstract Interior circulation pathways from the subtropics to the equator are markedly different in the Northern and Southern Hemispheres of the Pacific Ocean. In the North Pacific the pycnocline shoals and strengthens dramatically under the intertropical convergence zone, separating the North Equatorial Current from the North Equatorial Countercurrent. While the high potential vorticity between these currents would intuitively seem to inhibit meridional water-property exchange between the subtopics and the equator, transient tracer analyses and some modeling studies have suggested an interior pathway from the subtropics to the equator in the pycnocline of the central North Pacific. This study delineates this pathway and estimates an upper bound for its magnitude at 5 (±1) × 109 kg s−1. In contrast, the southern branch of the South Equatorial Current clearly brings pycnocline water estimated at 15 (±1) × 109 kg s−1 from the southern subtropics directly to the equator in the South Pacific through an interi.
University of Birmingham Cognitive Behavioural Relating Therapy (CBRT) for Voice Hearers: A Case Study

Background: There has been a recent focus on the interpersonal nature of the voice hearing experience, with studies showing that similar patterns of relating exist between voice hearer and voice as between voice hearer and social others. Two recent therapeutic approaches to voices, Cognitive Therapy for Command Hallucinations and Relating Therapy, have been developed to address patterns of relating and power imbalances between voice hearer and voice. Aims: This paper presents a novel intervention that combines elements of these two therapies, named Cognitive Behavioural Relating Therapy (CBRT). Method: The application of CBRT is illustrated through a clinical case study. Results: The clinical case study showed changes in patterns of relating, improved self-esteem and reductions in voice-related distress. Conclusions: The outcomes provide preliminary support for the utility of CBRT when working with voice hearers.
Detection in Data Streams

In data streams new classes can appear over time due to changes in the data statistical distribution. Consequently, models can become outdated, which requires the use of incremental learning algorithms capable of detecting and learning the changes over time. However, when a single classiﬁcation model is used for novelty detection, there is a risk that its bias may not be suitable for new data distributions. A solution could be the combination of several models into an ensemble. Besides, because models can only be updated when labeled data arrives, we propose two unsupervised ensemble approaches: one combining clustering partitions using the same clustering technique; and other using diﬀerent clustering techniques. We compare the performance of the proposed methods with well known novelty detection algorithms. The meth-ods were tested on datasets commonly used in the novelty detection literature. The experimental results show that proposed ensembles have competitive performance for novelty detection in data streams.
Biochemical changes in sunflower plants infected by Alternaria leaf blight

Alternaria leaf blight of sunflower has been considered as a potentially destructive disease. Due to cons of using chemical pesticides, in this current study we are using eco-friendly approach such as compost tea and seaweed formulation for the control of Alternaria disease. Compost tea is a liquid extract made from compost that contains a variety of nutrients, growth compounds and beneficial microorganisms. The microrganisms present in the compost tea produce biomolecules with antibiosis potential which contributes to disease suppression. Foliar spray of compost tea (1:10) @ 30, 45 DAS and propiconazole @ 1 mlL -1 at 60 DAS showed increased defense enzymes such as superoxide dismutase (39.47 µg/50 per cent inhibition) and peroxidase (16.86 µg/min/mg protein) when compared to superoxide dismutase (59.37 µg/50 per cent inhibition) and peroxidase (10.76 µg/min/mg protein) in control plants. Secondary metabolites such as phenolics (67.92 mg/g FW) and flavonoids (60.01 mg/g FW) was maximum in foliar spray of compost tea (1:10) @ 30, 45 DAS and propiconazole @ 1 mlL -1 at 60 DAS when compared to phenolics (57.48 mg/g FW) and flavonoids (41.87 mg/g FW) in control plants. This study demonstrated that foliar spray of compost tea and propiconazole can be used effectively for the management of Alternaria blight in fields as it exhibited more defense enzyme activity and increased growth and yield parameters.
FuzzyCSampling: A Hybrid fuzzy c-means clustering sampling strategy for imbalanced datasets

: Classification model with imbalanced datasets is recently one of the most researched areas in machine learning applications since they induce to the emergence of low-performing machine learning models. The imbalanced datasets occur if target variables have an uneven number of examples in a dataset. The most prevalent solutions to imbalanced datasets can be categorized as data preprocessing, ensemble techniques, and cost-sensitive learning. In this article, we propose a new hybrid approach for binary classification, named FuzzyCSampling, which aims to increase model performance by ensembling fuzzy c-means clustering and data sampling solutions. This article compares the proposed approaches’ results not only to the base model built on an imbalanced dataset but also to the previously presented state-of-the-art solutions undersampling, SMOTE oversampling, and Borderline Smote Oversampling. The model evaluation metrics for the comparison are accuracy, roc_auc score, precision, recall and F1-score. We evaluated the success of the brand-new proposed method on three different datasets having different imbalanced ratios and for three different machine learning algorithms (k-nearest neighbors algorithm, support vector machines and random forest). According to the experiments, FuzzyCSampling is an effective way to improve the model performance in the case of imbalanced datasets.
1 . 1 The XGRIND Query-friendly Compressor

XML documentsareinherentlyextremelyverbosesincethe“schema”is repeatedfor every“record” in the document. While a variety of compressorsareavailable to addressthis problem,they arenot designedto supportdirectqueryingof thecompressedocument,a usefulfeaturefrom a databaseperspecti ve. In thispaper , weproposeanew compressiontool calledXGrind, thatdirectlysupportsqueries in the compressed omain. A specialfeatureof XGrind is that the compressed ocumentretainsthe structureof the original document,permitting reuseof the standardXML techniquesfor processing thecompressedocument.Performanceevaluationover a varietyof XML documentsanduserqueries indicatesthatXGrind simultaneouslydeliversimprovedqueryprocessingtimesandreasonablecompressionratios.
Thiolutin has complex effects in vivo but is a direct inhibitor of RNA polymerase II in vitro

Abstract Thiolutin is a natural product transcription inhibitor with an unresolved mode of action. Thiolutin and the related dithiolopyrrolone holomycin chelate Zn2+ and previous studies have concluded that RNA Polymerase II (Pol II) inhibition in vivo is indirect. Here, we present chemicogenetic and biochemical approaches to investigate thiolutin's mode of action in Saccharomyces cerevisiae. We identify mutants that alter sensitivity to thiolutin. We provide genetic evidence that thiolutin causes oxidation of thioredoxins in vivo and that thiolutin both induces oxidative stress and interacts functionally with multiple metals including Mn2+ and Cu2+, and not just Zn2+. Finally, we show direct inhibition of RNA polymerase II (Pol II) transcription initiation by thiolutin in vitro in support of classical studies that thiolutin can directly inhibit transcription in vitro. Inhibition requires both Mn2+ and appropriate reduction of thiolutin as excess DTT abrogates its effects. Pause prone, defective elongation can be observed in vitro if inhibition is bypassed. Thiolutin effects on Pol II occupancy in vivo are widespread but major effects are consistent with prior observations for Tor pathway inhibition and stress induction, suggesting that thiolutin use in vivo should be restricted to studies on its modes of action and not as an experimental tool.
H3K9me regulates heterochromatin silencing through incoherent feedforward loops

Histone H3 lysine-9 methylation (H3K9me) is associated with condensed and transcriptionally inactive heterochromatin1. Although it has long been known that H3K9me silences transcription to control a wide variety of biological phenomena in many eukaryotic species2,3, how the silencing is regulated under the control of H3K9me is still largely unclear. Moreover, how cells delimit regions with H3K9me to avoid silencing essential genes remains unexplored. Here, using Arabidopsis genetic systems that induce H3K9me2 and its associated non-CG DNA methylation (mCH) in the transcribed region of genes de novo, we show that the accumulation of H3K9me2/mCH paradoxically also leads to the deposition of the euchromatic mark H3K36me3. This induction of H3K36me3 depends on a SET domain methyltransferase, ASHH3, and brings about anti-silencing by preventing the demethylation of H3K4me1 by LDL2, which mediates transcriptional silencing downstream of H3K9me2/mCH4. H3K9me2/mCH-driven antagonistic actions of ASHH3-H3K36me3 and LDL2-H3K4me1-loss also regulate the de novo silencing of reactivated transposable elements (TEs). These results demonstrate that H3K9me2 both facilitates and impedes silencing, and the incoherent feedforward loops fine-tune the fate of genes and TEs. Our results illuminate a novel elaborate mechanism for partitioning chromatin domains and provide insights into the molecular basis underlying natural epigenetic variation.
Aging in zebrafish is associated with reduced locomotor activity and strain-dependent changes in predator avoidance behaviors related to anxiety

Aging is associated with a wide range of physiological and behavioral changes in many species. Like humans, zebrafish exhibit gradual senescence, and thus may be a useful model organism for identifying evolutionarily conserved mechanisms related to aging. Here, we compared behavior in the novel tank test of young (6-month-old) and middle aged (12-month-old) zebrafish from two strains (TL and TU) and both sexes. We find that this modest age difference results in a reduction in locomotor activity and strain dependent changes in predator avoidance behaviors related to anxiety. Older TL fish have an elevation in bottom dwelling whereas older TU fish have a decrease in thigmotaxis. We found no consistent effects of age on either short-term (within session) or long-term (1 day later) habituation to the novel tank. Our findings support the use of zebrafish for the study of how age affects locomotion and how genetics interacts with age to alter the regulation of emotional behaviors in response to novelty.
Structural determinants of pure antiestrogenicity

Inhibitory activities of antiestrogens on estrogen receptor alpha (ERα) range from mixed antagonism/agonism (selective ER modulators; SERMs) to complete antiestrogenicity associated with accelerated ERα turnover (selective ER degraders; SERDs). Here, we show using a panel of SERMs, SERDs and a PROTAC that efficient induction of ERα SUMOylation better accounts for complete transcriptional repression than increased suppression of coactivator recruitment or accelerated ERα degradation. Antiestrogen-induced ERα SUMOylation depends on the hydrophobicity of N-terminal residues of ligand binding domain (LBD) helix 12 (H12). L536 mutations, including those occurring in endocrine therapy-resistant breast cancer, abolished SUMOylation with all antiestrogens. Structures of the L536S human ERα LBD bound to fulvestrant analogs and molecular dynamics simulations predict dynamic side chain interactions with wild-type ERα H12 in the coactivator-binding groove and model the impact of L536 mutations. Together, our results show that induced SUMOylation contributes to the complete suppression of ERα activity and provide insights into its structural determinants.
A practical low-dimensional feature vector generation method based on wavelet transform for psychophysiological signals

: High-dimensional feature vectors entail computational cost and computational complexity. However, a successful classification can be obtained with an optimally sized feature vector consisting of distinctive features. With the widespread use of the internet and mobile devices, the need for systems with low computational costs is increasing day by day. In this study, starting from the idea that each motor imagery is represented as a subject-specific pattern in the brain, we propose a new and practical method that can generate a low-dimensional feature vector based on wavelet transform. The feature vector is obtained from the correlation between each trial and each class average. To investigate the effect of possible temporal shifts in the trial signals, the proposed method is analyzed with signal segments with different starting points and lengths. The effect of these signal segments on classification is shown. The proposed feature extraction approach is tested on two different datasets and the classification results are presented in comparison with previous studies. With the method proposed in this study, much lower-dimensional feature vectors are obtained compared to previous studies and very satisfactory results are obtained. It is observed that EEG signals related to motor imagery in the brain have a subject-specific pattern, and this pattern is successfully classified with a feature vector consisting of only 1 feature per class.
Creating Finite Element Models of Facial Soft Tissue

Physically-based animation techniques enable more realistic and accurate animation to be created. Such approaches require the creation of a complex simulation model that, for computer graphics applications, can ef-ﬁciently produce realistic-looking animations. We present a process to automatically create animatable non-conforming hexahedral ﬁnite element (FE) simulation models of facial soft tissue, including automatic computation of skin layers and element material properties, muscle properties and boundary conditions, making them immediately ready for simulation. Using the GPU, the detailed models can simulate complex gross and ﬁne-scale behaviour, such as wrinkling. Our process can also be used to create a multi-layered FE model of any object (not just soft tissue).