Miracle-dz/UniFAR-FTUs huggingface dataset:
Mass Adoption of NATs: Survey and experiments on carrier-grade NATs

In recent times, the prevalence of home NATs and the widespread implementation of Carrier-Grade NATs have posed significant challenges to various applications, particularly those relying on Peer-to-Peer communication. This paper addresses these issues by conducting a thorough review of related literature and exploring potential techniques to mitigate the problems. The literature review focuses on the disruptive effects of home NATs and CGNATs on application performance. Additionally, the study examines existing approaches used to alleviate these disruptions. Furthermore, this paper presents a comprehensive guide on how to puncture a NAT and facilitate direct communication between two peers behind any type of NAT. The techniques outlined in the guide are rigorously tested using a simple application running the IPv8 network overlay, along with their built-in NAT penetration procedures. To evaluate the effectiveness of the proposed techniques, 5G communication is established between two phones using four different Dutch telephone carriers. The results indicate successful cross-connectivity with three out of the four carriers tested, showcasing the practical applicability of the suggested methods.
Towards Better Query Classification with Distribution-Diverse Multi-Expert Knowledge Distillation in JD Ads Search

Search query classification, as an effective way to understand user intents, is of great importance in real-world online ads systems. To ensure a lower latency, a shallow model ( e.g. FastText) is widely used for efficient online inference. However, the representation ability of the FastText model is insufficient, resulting in poor classification performance, especially on some low-frequency queries and tailed categories. Using a deeper and more complex model ( e.g. BERT) is an effective solution, but it will cause a higher online inference latency and more expensive computing costs. Thus, how to juggle both inference efficiency and classification performance is obviously of great practical importance. In this paper, we first show that with large parameters (17G), FastText exhibits powerful memory ability without increasing inference delay. It is just like a huge “online dictionary” that performs better on search queries that have been exposed in the historical data. However, for some unseen queries, BERT can generalize better benefits by its stronger semantic capabilities. By combining the advantages of both, we propose a novel Distribution-Diverse Multi-Expert (DDME) knowledge distillation framework to boost the classification performance
CNS therapeutics: Immune cells break the barriers

Peripheral immune cells can be seen as attractive vectors and drug carriers for central nervous system therapeutics because these cells have unique properties that allow them to migrate across the blood-brain barrier, enabling drug delivery to brain regions that are inaccessible to free drugs. Description Immune cell carriers enable targeted drug delivery to previously inaccessible brain regions through their capacity to cross the blood-brain barrier.
On the Use of the Force-Restore SVAT Model Formulation for Stratified Soils

Abstract An approach to simulate soil moisture content with the force–restore soil–vegetation–atmosphere transfer (SVAT) model in the case of stratified soils is proposed. Typical soil profiles possess marked variation in soil hydraulic properties from the soil surface to the base of the root zone. The force–restore method is extensively used for land surface modeling in atmospheric models but without any specific consideration for dealing with stratified soils. Drainage from and recharge to the near-surface soil layer is classically estimated on the basis of the volumetric soil moisture differences between the near surface and lower root zone, with an adjustment for gravitational effects. However, moisture differences do not relate uniquely to differences in hydraulic potentials when the soil properties are vertically inhomogeneous. As a consequence, the classical force–restore formulation does not correctly represent vertical fluxes, and it results in biased time series of predicted near-surface soil mo.
RudLOV—a new optically synchronized cargo transport method reveals unexpected effect of dynasore

Live imaging of secretory cargoes is a powerful method for understanding the mechanisms of membrane trafficking. Inducing the synchronous release of cargoes from an organelle is a key for enhancing microscopic observation. We developed an optical cargo-releasing method named as retention using dark state of LOV2 (RudLOV), which enables exceptional spatial, temporal, and quantity control during cargo release. A limited amount of cargo-release using RudLOV successfully visualized cargo cisternal-movement and cargo-specific exit sites on the Golgi/trans-Golgi network. Moreover, by controlling the timing of cargo-release using RudLOV, we revealed the canonical and non-canonical effects of the well-known dynamin inhibitor dynasore, which inhibits early-Golgi but not late-Golgi transport and exit from the trans-Golgi network where dynamin-2 is active. Accumulation of COPI vesicles at the cis-side of the Golgi stacks in dynasore-treated cells suggests that dynasore targets COPI-uncoating/tethering/fusion machinery in the early-Golgi cisternae or endoplasmic reticulum but not in the late-Golgi cisternae. These results provide insight into the cisternal maturation of Golgi stacks.
Biobank-scale inference of multi-individual identity by descent and gene conversion

We present a method for efficiently identifying clusters of identical-by-descent haplotypes in biobank-scale sequence data. Our multi-individual approach enables much more efficient collection and storage of identity by descent (IBD) information than approaches that detect and store pairwise IBD segments. Our method’s computation time, memory requirements, and output size scale linearly with the number of individuals in the dataset. We also present a method for using multi-individual IBD to detect alleles changed by gene conversion. Application of our methods to the autosomal sequence data for 125,361 White British individuals in the UK Biobank detects more than 9 million converted alleles. This is 2900 times more alleles changed by gene conversion than were detected in a previous analysis of familial data. We estimate that more than 250,000 sequenced probands and a much larger number of additional genomes from multi-generational family members would be required to find a similar number of alleles changed by gene conversion using a family-based approach.
A proteogenomic pipeline for the analysis of protein biosynthesis errors in the human pathogen Candida albicans

Candida albicans is a diploid pathogen known for its ability to live as a commensal fungus in healthy individuals, but causing both superficial infections and disseminated candidiasis in immunocompromised patients where it is associated with high morbidity and mortality. Its success in colonizing the human host is attributed to a wide range of virulence traits that modulate interactions between the host and the pathogen, such as optimal growth rate at 37°C, the ability to switch between yeast and hyphal forms and a remarkable genomic and phenotypic plasticity. A fascinating aspect of its biology is a prominent heterogeneous proteome that arises from frequent genomic rearrangements, high allelic variation, and high levels of amino acid misincorporations in proteins. The latter leads to increased morphological and physiological phenotypic diversity of high adaptive potential, but the scope of such protein mistranslation is poorly understood due to technical difficulties in detecting and quantifying amino acid misincorporation events in complex proteomic samples. To address this question, we have developed and optimized mass spectrometry and bioinformatics pipelines capable of identifying low-level amino acid misincorporation events at the proteome level. We have also analysed the proteomic profile of an engineered C. albicans strain that exhibits high level of leucine misincorporation at protein CUG sites and employed an in vivo quantitative gain-of-function fluorescence reporter system to validate our MS/MS data. The data show that C. albicans misincorporates amino acids above the background level at protein sites of diverse codons, particularly at CUG sites, confirming our previous data on the quantification of leucine incorporation at single CUG sites of recombinant reporter proteins. The study also demonstrates that increasing misincorporation of Leucine at CUG sites does not alter the translational fidelity of the other codons. These findings advance existing knowledge on amino acid misincorporations in C. albicans and add a new dimension to the remarkable capacity of this fungus to diversify its proteome.
Utilizing gene co-expression networks with the rat kidney TXG-MAPr tool to enhance safety assessment, biomarker identification and human translation

Toxicogenomic data represent a valuable source of biological information at molecular and cellular level to understand unanticipated organ toxicities. Weighted gene co-expression networks analysis can reduce the complexity of gene-level transcriptomic data to a set of biological response-networks useful for providing insights into mechanisms of drug-induced adverse outcomes. In this study, we have built co-regulated gene networks (modules) from the TG-GATEs rat kidney datasets consisting of time- and dose-response data for 41 compounds, including nephrotoxicants. Data from the 347 modules were incorporated into the rat kidney TXG-MAPr web tool, a user-friendly interface that enables visualization and analysis of module perturbations, quantified by a module eigengene score (EGS) for each treatment condition. Several modules annotated for cellular stress, renal injury and inflammation were statistically associated with concurrent renal pathologies, including modules that contain both well-known and novel renal biomarker genes. In addition, many rat kidney modules contain well annotated, robust gene networks that are preserved in other transcriptome datasets, suggesting that these biological networks translate to other (drug-induced) kidney injury cases. Moreover, preservation analysis of human kidney transcriptomic data provided a quantitative metric to assess the likelihood that rat kidney modules, and the associated biological interpretation, translate from non-clinical species to human. In conclusion, the rat kidney TXG-MAPr enables uploading and analysis of kidney gene expression data in the context of rat kidney co-expression networks, which could identify possible safety liabilities and/or mechanisms that can lead to adversity for chemical or drug candidates. Translational Statement Gene co-expression networks (modules) were generated using rat kidney toxicogenomics data, which reduced data complexity and retained quantitative mechanisms to enhance safety assessment. Several stress, injury and inflammation modules were statistically associated with renal pathologies, useful for biomarker identification. Moreover, many rat kidney modules contained well-annotated, robust gene-networks that were preserved in human patients transcriptome data after renal transplantation, suggesting that these biological networks translate to human relevant kidney-injury. So, the rat kidney TXG-MAPr tool enables transcriptome analysis in the context of kidney co-expression networks, which could identify chemical-induced safety liabilities and/or mechanisms leading to adversity, relevant for human risk-assessment.
Brain Charts for People Living with Multiple Sclerosis

Multiple sclerosis (MS) is associated with brain volume loss throughout the disease course. Currently available automated segmentation methods can measure total brain volume as well as ventricular volume, which has been advocated as a robust surrogate for brain volume based on clinically acquired magnetic resonance imaging (MRI). However, brain and ventricle volumes change naturally with age and may be susceptible to biases from differences in acquisition hardware, imaging protocol, and image quality, in addition to statistical biases such as regression to the mean. In this work, brain charts for people living with MS were established that account for patient biological sex, age, and differences in acquisition and image quality. 379 subjects were imaged longitudinally at 5 MS centers using 13 MRI scanner models from 2 scanner manufacturers employing a variety of protocols that included T1-weighted and T2-weighted FLAIR imaging. Generalized Additive Models for Location Scale and Shape (GAMLSS) were employed, and scanner metadata as well as automated assessments of image quality were modeled. Cross-sectional brain charts and conditional, longitudinal brain charts were estimated separately in female and male participants resulting in interpretable and intuitive centile estimates. These findings indicate that brain charts for people living with MS are a promising method for turning quantitative volumetrics into actionable knowledge about a patient’s disease. Highlights Interpreting observed changes in brain volume can be challenging due to statistical biases including regression to the mean. Brain size changes naturally with age and may be susceptible to biases associated with acquisition hardware, imaging protocol, and image quality. Brain charts for people living with MS are a promising method for translating quantitative volumetrics into interpretable knowledge about a patient’s disease.
Longitudinal stability of individual brain plasticity patterns in blindness

The primary visual cortex (V1) in individuals born blind is engaged in a wide spectrum of tasks and sensory modalities, including audition, touch, language, and memory. This widespread involvement raises questions regarding the constancy of its role and whether it might exhibit flexibility in its function over time, connecting to diverse network functions in response to task-specific demands. This would suggest that reorganized V1 takes on a role similar to cognitive multiple-demand system regions. Alternatively, it is possible that the varying patterns of plasticity observed in the blind V1 can be attributed to individual factors, whereby different blind individuals recruit V1 for different functions, highlighting the immense idiosyncrasy of plasticity. In support of this second account, we have recently shown that V1 functional connectivity varies greatly across blind individuals. But do these represent stable individual patterns of plasticity or merely instantaneous changes, for a multiple-demand system now inhabiting V1? Here we tested if individual connectivity patterns from the visual cortex of blind individuals are stable over time. We show that over two years, fMRI functional connectivity from the primary visual cortex is unique and highly stable in a small sample of repeatedly sampled congenitally blind individuals. Further, using multivoxel pattern analysis, we demonstrate that the unique reorganization patterns of these individuals allow decoding of participant identity. Together with recent evidence for substantial individual differences in visual cortex connectivity, this indicates there may be a consistent role for the visual cortex in blindness, which may differ for each individual. Further, it suggests that the variability in visual reorganization in blindness across individuals could be used to seek stable neuromarkers for sight rehabilitation and assistive approaches.
TRAFICA: Improving Transcription Factor Binding Affinity Prediction using Deep Language Model on ATAC-seq Data

In silico prediction of transcription factor (TF) binding affinity plays a vital role in determining TF binding preferences and understanding gene regulation. Many existing tools utilize known TF-DNA binding data to train conventional machine learning and deep learning models to predict TF-DNA binding affinities. The majority of these tools do not consider the natural preferences of DNA sequences binding to TFs, which could be influenced by chromatin accessibility. In this study, we developed TRAFICA, a deep language model to predict TF-DNA binding affinities by integrating chromatin accessibility from ATAC-seq and known TF-DNA binding data. We pre-trained TRAFICA on an integrated ATAC-seq dataset with over 13 million nucleotide sequences in a self-supervised manner to learn potential TF-DNA binding preferences and contextual relationships within DNA sequences. TRAFICA was fine-tuned using PBM and HT-SELEX datasets to predict in vitro TF-DNA binding affinities. We also implemented AdapterFusion to enhance its ability to predict in vivo TF-DNA binding affinities. We observed TRAFICA significantly outperformed the six existing tools in predicting in vitro TF-DNA binding affinities and was comparable with the best tool on in vivo prediction.
link-ancestors: fast simulation of local ancestry with tree sequence software

Summary It is challenging to simulate realistic tracts of genetic ancestry on a scale suitable for simulation based inference. We present an algorithm that enables this information to be extracted efficiently from tree sequences produced by simulations run with msprime and SLiM. Availability and Implementation A C-based implementation of the link-ancestors algorithm is in tskit (https://tskit.dev/tskit/docs/stable/). We also provide a user-friendly wrapper for link-ancestors in tspop, a Python-based utility package. Contact gtsambos@uw.edu. Supplementary information Technical details of link-ancestors are in the Supplementary Information. Documentation for the tspop package is at http://tspop.readthedocs. io/.
Knockout of cyclin dependent kinases 8 and 19 leads to depletion of cyclin C and suppresses spermatogenesis and male fertility in mice

Paralogs CDK8 and CDK19 are regulatory kinases associated with the transcriptional Mediator complex. We have for the first time generated mice with the systemic inducible Cdk8 knockout on the background of Cdk19 constitutive knockout. Cdk8/19 double knockout (DKO) males, but not single Cdk8 and Cdk19 KO, had an atrophic reproductive system and were infertile. The DKO males lacked postmeiotic spermatids and spermatocytes after meiosis I pachytene. Testosterone levels were decreased whereas the amounts of the luteinizing hormone were unchanged. Single cell RNA sequencing showed marked differences in the expression of steroidogenic genes (such as Cyp17a1, Star and Fads) in Leydig cells concomitant with alterations in Sertoli cells and spermatocytes likely associated with impaired synthesis of steroids. Star and Fads were also downregulated in cultivated Leydig cells after DKO. The treatment of primary Leydig cells culture with a CDK8/19 inhibitor did not induce the same changes in gene expression as DKO, and prolonged treatment of mice with a CDK8/19 inhibitor did not affect the size of testes. DKO, in contrast to single knockouts or treatment with a CDK8/19 kinase inhibitor, led to depletion of cyclin C (CcnC), the binding partner of CDK8/19 that has been implicated in CDK8/19-independent functions. This suggests that the observed phenotype was likely mediated through kinase-independent activities of CDK8/19, such as CcnC stabilization.
The evolutionary conserved choroid plexus sustains the homeostasis of brain ventricles in zebrafish

The choroid plexus produces cerebrospinal fluid (CSF) by transport of electrolytes and water from the vasculature to the brain ventricles. The choroid plexus plays additional roles in brain development and homeostasis by secreting neurotrophic molecules, and by serving as a CSF-blood barrier and immune interface. Prior studies have identified transporters on the epithelial cells that transport water and ions into the ventricles and tight junctions involved in the CSF-blood barrier. Yet, how the choroid plexus epithelial cells maintain the brain ventricle system and control brain physiology remain unresolved. To provide novel insights into the physiological roles of the choroid plexus, we use juvenile and adult zebrafish as model systems. Upon histological and transcriptomic analyses, we first identified that the zebrafish choroid plexus is highly conserved with the mammalian choroid plexus and that it expresses all transporters necessary for CSF secretion. Using novel genetic lines, we also identified that the choroid plexus secretes proteins into the CSF. Next, we generated a transgenic line allowing us to ablate specifically the epithelial cells in the choroid plexus. Using the ablation system, we identified a reduction of the ventricular sizes, but no alterations of the CSF-blood barrier. Altogether, our findings identified that the zebrafish choroid plexus is evolutionarily conserved and critical for maintaining the size and homeostasis of the brain ventricles. Graphical abstract Highlights The zebrafish choroid plexus has similar anatomical features with the mammalian choroid plexus. The expression of choroid plexus transporters involved in CSF secretion is evolutionarily conserved across vertebrates. Generation of a novel choroid plexus specific driver line shows that the choroid plexus epithelial cells secrete proteins into CSF. Ablation of the choroid plexus decreases the size of the brain ventricles.
IC-VAE: A Novel Deep Learning Framework for Interpreting Multiplexed Tissue Imaging Data

Interpreting protein expression in multiplexed tissue imaging data presents a significant challenge due to the high dimensionality of the resulting images, the variety of intracellular structures, cell shapes resulting from 2-D tissue sectioning, and the presence of technological noise and imaging artifacts. Here, we introduce the Information-Controlled Variational Autoencoder (IC-VAE), a deep generative model designed to tackle this challenge. The contribution of IC-VAE to the VAE framework is the ability to control the shared information among latent subspaces. We use IC-VAE to factorize each cell’s image into its true protein expression, various cellular components, and background noise, while controlling the shared information among some of these components. Compared with other normalization methods, this approach leads to superior results in downstream analysis, such as analyzing the expression of biomarkers, classification for cell types, or visualizing cell clusters using t-SNE/UMAP techniques.
A microphysiological system for parallelized morphological and electrophysiological read-out of 3D neuronal cell culture

Three-dimensional in vitro models in microfluidic systems are promising tools for studying cell biology, with complex models using multiple cell types combined with high resolution imaging. Neuronal models demand electrical readout of the activity of networks of single neurons, yet classical planar microelectrode arrays struggle to capture extracellular action potentials when neural soma are suspended distant from the microelectrodes. This study introduces sophisticated microfluidic microelectrode arrays, specifically tailored for electrophysiology of 3D neuronal cultures. Using multilayer photolithography of permanent epoxy photoresists, we developed devices having 12 independent culture modules in a convenient format. Each module has two adjacent compartments for hydrogel-based 3D cell culture, with tunnels allowing projection of neurites between compartments. Microelectrodes integrated in the tunnels record action potentials as they pass between the compartments. Mesh ceilings separate the compartments from overlying wells, allowing for simple cell seeding and later nutrient, gas and waste exchange and application of test substances. Using these devices, we have demonstrated 3D neuronal culture, including electrophysiological recording and live imaging. This microphysiological platform will enable high-throughput investigation of neuronal networks for investigation of neurological disorders, neural pharmacology and basic neuroscience. Further models could include cocultures representing multiple brain regions or innervation models of other organs.