Miracle-dz/UniFAR-FTUs huggingface dataset:
The fungal protein Jps1 facilitates unconventional protein secretion through a direct phosphoinositide interaction

Protein secretion is indispensable for essential cellular processes in eukaryotic cells, contributing significantly to nutrient acquisition, defense or communication. Alternative pathways bypassing the endomembrane system collectively referred to as unconventional secretion are gaining increasing attention. A number of important molecules such as cytokines, fibroblast growth factor or viral proteins are being exported through these mechanistically diverse pathways. In the fungal model Ustilago maydis, cytokinesis-dependent unconventional secretion mediates export of the chitinase Cts1 via the fragmentation zone. This membrane-rich compartment is formed during cytokinesis between mother and daughter cells. Recently, we identified Jps1, a previously uncharacterized protein, as a crucial factor for Cts1 localization and export. Combining biochemical experiments and in vivo studies, we here uncover two pivotal features of Jps1: phosphoinositide (PIP) binding and dimerization. Our findings reveal that Jps1 does not harbor a canonical PIP-binding domain but instead specifically binds to PI(4,5)P2, likely via basic residues. A conserved structural core domain of Jps1 mediates dimerization, while the flexible variable regions suggest potential diversification in different basidiomycetous species. The accumulation of Jps1 in the fragmentation zone, facilitated by its PIP affinity, provides a direct membrane recognition mechanism. This discovery sheds light on a previously unknown key feature of Jps1, elucidating its role in supporting Cts1 secretion, and representing a crucial step towards understanding the broader implications of unconventional secretion in eukaryotic cells.
PTCHD1 interacts with the SNARE-associated protein SNAPIN in vitro via its first exoplasmic loop

Patched domain-containing 1 (PTCHD1) is a susceptibility gene for autism spectrum disorder (ASD) and intellectual disability (ID). PTCHD1 is predicted to encode a multi-pass protein consisting of 12 transmembrane domains, two large exoplasmic loops, and a C-terminal PDZ-binding domain. PTCHD1 contains sequence homology with the Hedgehog signaling pathway repressors Patched domain-containing-1 (PTCH1) and -2 (PTCH2), as well as the cholesterol trafficking protein Niemann-Pick disease type C1 (NPC1). Despite this homology, the functional role of PTCHD1 in brain development remains elusive. Studies have sought to characterize the function of PTCHD1 by elucidating its neural network of interacting proteins. Using a yeast two-hybrid assay, we have identified a novel interaction between the first exoplasmic loop of PTCHD1 and the SNARE-associated protein SNAPIN, which is implicated in synaptic vesicle exocytosis. Clinically-associated missense variants within this region of PTCHD1 did not disrupt SNAPIN binding, indicating that the pathoetiology of these variants is unrelated to this interaction. However, several of these missense variants exhibited pronounced retention within the endoplasmic reticulum, and impaired trafficking to the plasma membrane, indicating a possible mechanism of pathogenicity. These data yield insights regarding the possible role of PTCHD1 in neurodevelopment and neurotransmission, as well as suggest a pathoetiological mechanism for numerous clinical missense variants, providing a platform for subsequent diagnostic assays, and an avenue for possible therapeutic intervention.
Limited Cell-Autonomous Anticancer Mechanisms in Long-Lived Bats

Bats are remarkably long-lived for their size with many species living more than 20-40 years, suggesting that they possess efficient anti-aging and anti-cancer defenses. Here we investigated requirements for malignant transformation in primary bat fibroblasts in four bat species - little brown bat (Myotis lucifugus), big brown bat (Eptesicus fuscus), cave nectar bat (Eonycteris spelaea) and Jamaican fruit bat (Artibeus jamaicensis) – spanning the bat evolutionary tree and including the longest-lived genera. We show that bat fibroblasts do not undergo replicative senescence and express active telomerase. Bat cells displayed attenuated stress induced premature senescence with a dampened secretory phenotype. Unexpectedly, we discovered that bat cells could be readily transformed by only two oncogenic perturbations or “hits”: inactivation of either p53 or pRb and activation of oncogenic RASV12. This was surprising because other long-lived mammalian species require up to five hits for malignant transformation. Additionally, bat fibroblasts exhibited increased p53 and MDM2 transcript levels, and elevated p53-dependent apoptosis. The little brown bat showed a genomic duplication of the p53 gene. We hypothesize that bats evolved enhanced p53 activity through gene duplications and transcriptional upregulation as an additional anti-cancer strategy, similar to elephants. In summary, active telomerase and the small number of oncogenic hits sufficient to malignantly transform bat cells suggest that in vivo bats rely heavily on non-cell autonomous mechanisms of tumor suppression.
Designed fluorescent protein cages as fiducial markers for targeted cell imaging

Understanding how proteins function within their cellular environments is essential for cellular biology and biomedical research. However, current imaging techniques exhibit limitations, particularly in the study of small complexes and individual proteins within cells. Previously, protein cages have been employed as imaging scaffolds to study purified small proteins using cryo-electron microscopy (cryo-EM). Here we demonstrate an approach to deliver designed protein cages – endowed with fluorescence and targeted binding properties – into cells, thereby serving as fiducial markers for cellular imaging. We used protein cages with anti-GFP DARPin domains to target a mitochondrial protein (MFN1) expressed in mammalian cells, which was genetically fused to GFP. We demonstrate that the protein cages can penetrate cells, are directed to specific subcellular locations, and are detectable with confocal microscopy. This innovation represents a milestone in developing tools for in-depth cellular exploration, especially in conjunction with methods such as cryo-correlative light and electron microscopy (cryo-CLEM).
Gut microbes of the cecum versus the colon drive more severe lethality and multi-organ damage

An intestinal perforation or puncture leads to a high risk of sepsis-associated morbidity. A perforation initiates the transfer of the intestinal contents (ICs) to the peritoneal cavity, leading to abdominal infections and varying with different prognoses. However, the mechanisms associated with different perforations in the cecum and colon remain unknown. We sought to examine how different gut flora contribute to prognoses in different intestinal perforation sites. We compared the microbiome of the ICs in the cecum and colon in a fecal-induced peritonitis mouse model. The results showed that cecum ICs developed more severe sepsis than colon ICs, including a shorter median survival time, increased biochemical indicators, more pathological changes in multiple organs and overwhelmed systematic inflammation. Moreover, our results demonstrated that cecum ICs hold more bacterial burden in unit weight than colon ICs, and the microbial communities differed between the ICs from the cecum and colon. A more detailed comparison of the two microbiome groups showed that the abundance of potentially pathogenic bacteria increased in the cecum ICs. Our data suggest that the sepsis severity developed by perforation was associated with bacterial burden and increased abundance of potentially pathogenic bacteria in the cecum. Our findings first compared the differences in the lethality associated with the ICs of the cecum and colon, which pointed out that the site of perforation could help providers predict the severity of sepsis.
Erythropoietin production in embryonic neural cells is controlled by hypoxia-inducible factors and histone deacetylases in an undifferentiated state

During mammalian development, production sites of the erythroid growth factor erythropoietin (EPO) shift from the neural tissues to the liver in embryos and to the adult kidneys. Embryonic neural EPO-producing (NEP) cells, a subpopulation of neuroepithelial and neural crest cells, express the Epo gene between embryonic day (E) 8.5 and E11.5 to promote primitive erythropoiesis in mice. While Epo gene expression in the liver and kidney is induced under hypoxic conditions through hypoxia-inducible transcription factor (HIF) 2α, the Epo gene regulatory mechanisms in NEP cells remain to be elucidated. This study confirms the presence of cells coexpressing the genes encoding EPO and HIF2α in E9.5 neural tubes, where the hypoxic microenvironment activates HIF1α. In human neural progenitors and mouse embryonic neural tissues, a HIF-activating compound upregulated EPO expression, and this induction was blocked by inhibiting HIFs. Additionally, a cell line of NEP cell derivatives that no longer expressed the Epo gene demonstrated that histone deacetylase inhibitors (HDACIs) reactivate EPO production while rejuvenating the cells. HDACIs also induced EPO gene expression in SK-N-BE(2)c human neuroblastoma cells and mouse primary neural crest cells. Thus, EPO production is controlled by epigenetic mechanisms and hypoxia signaling in an immature state of hypoxic NEP cells.
MultiMatch: Geometry-Informed Colocalization in Multi-Color Super-Resolution Microscopy

With recent advances in multi-color super-resolution light microscopy it has become possible to simultaneously visualize multiple subunits within complex biological structures at nanometer resolution. To opti-mally evaluate and interpret spatial proximity of stainings on such an image, colocalization analysis tools have to be able to integrate prior knowledge on the local geometry of the recorded biological complex. Here, we present MultiMatch to analyze the abundance and location of chain-like particle arrangements in multi-color microscopy based on multi-marginal optimal unbalanced transport methodology. Our object-based colocalization model statistically addresses the effect of incomplete labeling efficiencies enabling inference on existent, but not fully observ-able particle chains. We showcase that MultiMatch is able to consistently recover all existing chain structures in three-color STED images of DNA origami nanorulers and outperforms established geometry-uninformed triplet colocalization methods in this task in a simulation study. Further-more, MultiMatch also excels in the evaluation of simulated four-color STED images and generalizations to even more color channels can be immediately derived from our analysis. MultiMatch is provided as a user-friendly Python package comprising intuitive colocalization visual-izations and a computationally efficient network flow implementation.
HuD (ELAVL4) gain-of-function impairs neuromuscular junctions and induces apoptosis in in vitro and in vivo models of amyotrophic lateral sclerosis

Early defects at the neuromuscular junction (NMJ) are among the first hallmarks of the progressive neurodegenerative disease amyotrophic lateral sclerosis (ALS). According to the “dying back” hypothesis, disruption of the NMJ not only precedes, but is also a trigger for the subsequent degeneration of the motoneuron in both sporadic and familial ALS, including ALS caused by the severe FUS pathogenic variant P525L. However, the mechanisms linking genetic and environmental factors to NMJ defects remain elusive. By taking advantage of co-cultures of motoneurons and skeletal muscle derived from human induced pluripotent stem cells (iPSCs), we show that the neural RNA binding protein HuD (ELAVL4) may underlie NMJ defects and apoptosis in FUS-ALS. HuD overexpression in motoneurons phenocopies the severe FUSP525L mutation, while HuD knockdown in FUSP525L co-cultures produces phenotypic rescue. We validated these findings in vivo in a Drosophila FUS-ALS model. Neuronal-restricted overexpression of the HuD-related gene, elav, produces per se a motor phenotype, while neuronal-restricted elav knockdown significantly rescues motor dysfunction caused by FUS. Finally, we show that HuD levels increase upon oxidative stress in human motoneurons and in sporadic ALS patients with an oxidative stress signature. On these bases, we propose HuD as an important player downstream of FUS mutation in familial ALS, with potential implications for sporadic ALS related to oxidative stress.
Precision Tuning the Rust Memory-Safe Programming Language

Precision tuning is an increasingly common approach for exploiting the tradeoff between energy efficiency or speedup, and accuracy. Its effectiveness is particularly strong whenever the maximum performance must be extracted from a computing system, such as embedded platforms. In these contexts, current engineering practice sees a dominance of memory-unsafe programming languages such as C and C++. However, the unsafe nature of these languages has come under great scrutiny as it leads to significant software vulnerabilities. Hence, safer programming languages which prevent memory-related bugs by design have been proposed as a replacement. Amongst these safer programming languages, one of the most popular has been Rust. In this work we adapt a state-of-the-art precision tuning tool, TAFFO, to operate on Rust code. By porting the PolyBench/C benchmark suite to Rust, we show that the effectiveness of the precision tuning is not affected by the use of a safer programming language, and moreover the safety properties of the language can be successfully preserved. Specifically, using TAFFO and Rust we achieved up to a 15 × speedup over the base Rust code, thanks to the use of precision tuning.
Effect of an Aqueous Extract of a Combination of Nauclea latifolia Root and Acalypha torta Leaves on Heamatological Parameters

Aim: The safety of several commercially available herbs has recently come into question due to reports of adverse effects and potential interaction with prescribed drugs. This study was aimed at evaluating the subchronc toxicity of aqueous extract of a combination of Nauclea latifolia root and Acalypha torta leaves on some heamatological parameters of albino rats. Materials and Methods: The dry root and leaf samples of N. latifolia and A. torta respectively were collected, pulverized and mixed in the ratio of 5:1 respectively. Aqueous extract of the mixture was obtained after soaking in water for 24 hours and evaporating the filtrate to dryness using Rotary Evaporator. The Acute toxicity was assessed according to Lorke’s method to determine the Lethal Dose (LD50). Sub – chronic toxicological effects of 50.0 and 100.0 mg/kg body weight of the extract on heamatological indices were ascertained for 3 months at one month intervals. Thirty nine rats (120-150g) were used for the study and the extract was administered orally throughout the period of studies. Parameters were measured using standard methods. Result: Results showed that the LD50 was above 5000mg/kg body weight and no behavioural changes were observed within the 24 hours. Sub-chronic toxicity evaluation following administration of 50 and 100mg/kg body weight doses of the extracts showed non-significant changes (p>0.05) in the heamatological parameters when compared to the control. The results indicated no significant changes (p>0.05) in the packed cell volume (PCV), heamoglobin concentration (HB), total white blood cell count (TWBC) and white blood cell differential count when compared to the control. Conclusion: Even though further investigations are still needed, the present findings suggested that these doses of the aqueous extract of the mixture of N. latifolia root and A. torta leaf (5:1) do not have deleterious effects on the blood and blood forming tissues in rat.
Tailoring with Targeted Precision: Edit-Based Agents for Open-Domain Procedure Customization

How-to procedures, such as how to plant a garden, are now used by millions of users, but sometimes need customizing to meet a user’s specific needs, e.g., planting a garden without pesticides. Our goal is to measure and improve an LLM’s ability to perform such customization. Our approach is to test several simple multi-LLM-agent architectures for customization, as well as an end-to-end LLM, using a new evaluation set, called C USTOM P LANS , of over 200 WikiHow procedures each with a customization need. We find that a simple architecture with two LLM agents used sequentially performs best, one that edits a generic how-to procedure and one that verifies its executability, significantly outperforming (10.5% absolute) an end-to-end prompted LLM. This suggests that LLMs can be configured reasonably effectively for procedure customization. This also suggests that multi-agent editing architectures may be worth exploring further for other customization applications (e.g. coding, creative writing) in the future.
Data Quality Assessment: Challenges and Opportunities

Data-oriented applications, their users, and even the law require data of high quality. Research has broken down the rather vague notion of data quality into various dimensions, such as accuracy, consistency, and reputation, to name but a few. To achieve the goal of high data quality, many tools and techniques exist to clean and otherwise improve data. Yet, systematic research on actually assessing data quality in all of its dimensions is largely absent, and with it the ability to gauge the success of any data cleaning effort. It is our vision to establish a systematic and comprehensive framework for the (numeric) assessment of data quality for a given dataset and its intended use. Such a framework must cover the various facets that influence data quality, as well as the many types of data quality dimensions. In particular, we identify five facets that serve as a foundation of data quality assessment. For each facet, we outline the challenges and opportunities that arise when trying to actually assign quality scores to data and create a data quality profile for it, along with a wide range of technologies needed for this purpose.
SPATIO-TEMPORAL STOCHASTIC MODELLING OF SALINE DEPOSITION MEASURED BY BIOMONITORS

The input of sea salt to a coastal environment shows high variability in both space and time domains, hence the estimation of salt-tracing elements in biomonitors should account for either dimension. Furthermore, it is also a non-stationary process, because space variability strongly depends on the distance from the sea. Time variability is mainly dependent on the occurrence of precipitation events, with their leaching effect that causes a decrease of concentrations, and on the period of exposure to the atmosphere in dry conditions. The methodology presented herein deals with the application of kriging with external drift as an interpolation procedure for sodium accumulated by lichens, in a generalised space-time domain. The definition of an auxiliary variable is based on the description of the processes involved in the uptake of sodium from marine origin by epiphytic lichens, through a parametric model that features distance inland, precipitation intensity, and length of the dry period before sampling as major variability factors. Kriging with such an external drift yields better estimates of airborne salinity at ground level than ordinary kriging does, and such an enhanced performance can be checked out from the cross-validation results as well as from an observation of the corresponding, estimated maps.
Application of Online Visual-Spatial Training to Increase Visual-Spatial Ability and Growth Mindset of Engineering Students*

The preponderance of growth mindset intervention studies focus on elevating a growth mindset by teaching students that the mind is like a muscle and that it grows stronger through rigorous mental exercise. But, there is also the potential to elevate a growth mindset via strengthening intelligence. Spatial visualization promotes successful engineering performance and many college students would beneﬁt from improved visual-spatial ability. The primary objective of this study was to examine whether a brief online workshop that teaches visual-spatial skills (e.g., mental rotation) would increase both visual-spatial ability and a growth mindset for spatial intelligence. This study included 296 undergraduate mechanical, systems, industrial, and aerospace engineering students that participated in a total of 3.5 hours of a workshop that trained students in visual-spatial thinking over the course of 7 weeks. Outcome measures included pre/post Purdue Spatial Visualization Test-Visualization of Rotations (PSVT:R) and pre/post growth mindset for spatial intelligence. Paired sample t-tests indicated that students improved signiﬁcantly from pre to post-workshop on both mental rotations (Cohen’s d = 0.38) and growth mindset ( d = 0.33). Women improved as much as men on both measures. This study suggests that an online visual-spatial intervention can eﬃciently promote stronger visual-spatial ability and a growth mindset.
Harnessing the Speed and Accuracy of Machine Learning to Advance Cybersecurity

As cyber attacks continue to increase in frequency and sophistication, detecting malware has become a critical task for maintaining the security of computer systems. Traditional signature-based methods of malware detection have limitations in detecting complex and evolving threats. In recent years, machine learning (ML) has emerged as a promising solution to detect malware effectively. ML algorithms are capable of analyzing large datasets and identifying patterns that are difficult for humans to identify. This paper presents a comprehensive review of the state-of-the-art ML techniques used in malware detection, including supervised and unsupervised learning, deep learning, and reinforcement learning. We also examine the challenges and limitations of ML-based malware detection, such as the potential for adversarial attacks and the need for large amounts of labeled data. Furthermore, we discuss future directions in ML-based malware detection, including the integration of multiple ML algorithms and the use of explainable AI techniques to enhance the interpretability of ML-based detection systems. Our research highlights the potential of ML-based techniques to improve the speed and accuracy of malware detection, and contribute to enhancing cybersecurity.
R-PEAK DETECTION FROM NOISY ECG DATA USING MULTI-CHANNEL 1D-CNN WITH ACCEL-EROMETER INPUT

In order to prevent traffic accidents due to abrupt changes in the driver's health condition, we have proposed a non-contact type electrocardiographic sensor that monitors the electrocardiogram (ECG) of a driver holding a steering wheel while seated. However, the heart rate detection accuracy degrades while driving due to the lower signal-to-noise ratio (SNR) of the ECG caused by the noise from vehicle vibration and static electricity, among others. In this study, we propose a method of detecting R-peaks of the ECG from the low SNR ECG signal with high accuracy using a multi-channel one-dimensional convolutional neural network with accelerometer signals as an input. As the results, we achieved an F -score of 78.5% and a root-mean-square error (RMSE) of 1.99 ms. The R-peak detection performance was significantly improved when the input data length of around 1100 ms was chosen.
Direct 3D model-based object tracking with event camera by motion interpolation

—Event cameras are recent sensors that measure intensity changes in each pixel asynchronously. It is being used due to lower latency and higher temporal resolution compared to traditional frame-based camera. We propose a method of 3D model-based object tracking directly from events captured by event camera. To enable reliable and accurate tracking of objects, we use a new event representation and predict brightness increment images with motion interpolation. Results of object tracking show the new methods significantly improves tracking duration and robustness, both for perspective and fisheye cameras. Our implementation succeeds in tracking objects when the camera speed is reaching 2 m/s.