Miracle-dz/UniFAR-FTUs huggingface dataset:
POU1F1/Pou1f1 c.143-83A > G Variant Disrupts the Branch Site in Pre-mRNA and Leads to Dwarfism

Abstract POU Class 1 Homeobox1 (POU1F1/Pou1f1) is a well-established pituitary-specific transcription factor, and causes, when mutated, combined pituitary hormone deficiency in humans and mice. POU1F1/Pou1f1 has 2 isoforms: the alpha and beta isoforms. Recently, pathogenic variants in the unique coding region of the beta isoform (beta domain) and the intron near the exon–intron boundary for the beta domain were reported, although their functional consequences remain obscure. In this study, we generated mice carrying the Pou1f1 c.143-83A>G substitution that recapitulates the human intronic variant near the exon–intron boundary for the beta domain. Homozygous mice showed postnatal growth failure, with an average body weight that was 35% of wild-type littermates at 12 weeks, which was accompanied by anterior pituitary hypoplasia and deficiency of circulating insulin-like growth factor 1 and thyroxine. The results of RNA-seq analysis of the pituitary gland were consistent with reduction of somatotrophs, and this was confirmed immunohistochemically. Reverse transcription polymerase chain reaction of pituitary Pou1f1 mRNA showed abnormal splicing in homozygous mice, with a decrease in the alpha isoform, an increase in the beta isoform, and the emergence of the exon-skipped transcript. We further characterized artificial variants in or near the beta domain, which were candidate positions of the branch site in pre-mRNA, using cultured cell–basis analysis and found that only c.143-83A>G produced transcripts similar to the mice model. Our report is the first to show that the c.143-83A>G variant leads to splicing disruption and causes morphological and functional abnormalities in the pituitary gland. Furthermore, our mice will contribute understanding the role of POU1F1/Pou1f1 transcripts in pituitary development.
SensAE – A Tool to Explore Material-Touch-Emotions

Abstract Humans have always explored and interacted with their environment through touching surfaces. The sense of touch is an important part of human interaction and communication. It supports emotional development and wellbeing. But despite the relevance of touch in tactile experience, the touch of (textile) materials and its relationship to emotion has to date not received much attention. There is no tool or process to support textile designers evaluates emotional responses to the touch of textile materials. Designing with materials for overall wellbeing necessitates an understanding of the sensory modalities as well as consideration of the affective stage of what impacts material choices. This article provides a review of key background literature in understanding the complexity of the material-touch-emotion relationship, and the physical and psychological aspects of touching a material. Reflecting on workshops conducted, the Sensation-Appraisal-Emotion (SensAE) tool is presented to better understand the connection between the active touch of material surfaces and the emotional responses to that material touch. The article outlines the methodology for how the SensAE tool was developed, describing the tool, and benefits of using it. The SensAE tool explains the three stages in the material-touch-emotion elicitation process as sensation, appraisal and emotions. It encourages designers and users to consider first the sensation of actively touching the material- how “it” feels; to consider their appraisal of the sensation; and finally, their emotional response to the material- how “they” feel. The SensAE tool supports a user-centered design approach to be used as a guide enabling emotional connections to the touch of textile materials, thereby understanding psychological considerations surrounding sustainable material choices. The SensAE tool provides a way for designers to better assist their material choices consequently supporting a more empathic design process, to enable design for wellbeing.
On the Cauchy problem for the heat equation on Riemannian manifolds with conical singularities

We study the existence and regularity of solutions to the Cauchy problem for the inhomogeneous heat equation on compact Riemannian manifolds with conical singularities. We introduce weighted H\"older and Sobolev spaces with discrete asymptotics and we prove existence and maximal regularity of solutions to the Cauchy problem for the inhomogeneous heat equation, when the free term lies in a weighted parabolic H\"older or Sobolev space with discrete asymptotics. This generalizes a result previously obtained by Coriasco, Schrohe, and Seiler (Thm. 7.2 in Math. Z. 244 (2003), 235--269) by different means.
The first host-associated anaerobic isolate of Psychrilyobacter provides insights into its potential roles in the abalone gut

Gut bacteria are essential to their hosts, but few studies have focused on marine animals. Psychrilyobacter is frequently related to various marine animals, but the relationship with host remains unknown due to lack of host-associated isolate or genomic information. Here, we combined of high-throughput sequencing, isolating and genomic analyses to uncover its potential role in host abalone. The high-throughput sequencing and literature compiling results indicated that Psychrilyobacter is widely distributed in marine and terrestrial ecosystems with both host-associated and free-living lifestyles. It showed a strong preference for the guts of marine invertebrates, especially abalone, which generally persisted with high relative abundances. By mimicking the gut inner environment for enrichment, the first host-related pure culture of Psychrilyobacter was isolated from the abalone intestine. Phylogenetic, physiological and biochemical characterizations suggested that it represents a novel species named Psychrilyobacter haliotis B1. Carbohydrate utilization experiments and genomic evidence indicated that B1 is good at fermenting diverse host-food-related monosaccharides and disaccharides but not polysaccharides, implying its critical roles in downstream fermentation instead of upstream food degradation in the gut. Furthermore, this strain showed potential to colonize the gut and benefit the host via different strategies, such as short-chain fatty acids (SCFAs) generation by fermenting carbohydrates and amino acids, and the production of diverse vitamins and antibiotics to support the host growth and antipathogenicity. To our knowledge, strain B1 represents the first host-related pure culture of Psychrilyobacter, acting as a potential probiotic gut anaerobe dominating in diverse marine invertebrates. Importance Psychrilyobacter is a globally distributing bacterial genus and with an inhabiting preference for guts of marine invertebrates. Due to the difficulty of cultivation and the limited genomic information, its role in host remains largely unknown. We isolated the first host-associated Psychrilyobacter species from abalone gut and uncovered its functional potentials to the host through different mechanisms. Our findings provide some insights into the understanding of host-microbe interactions on a core taxon with the marine invertebrates, and the isolate has an application prospect as a probiotic in protection of marine animals.
Tissue-specific overexpression of the double-stranded RNA transporter SID-1 limits lifespan in C. elegans

Intertissue RNA transport has emerged as a novel signaling mechanism. In C. elegans, this is conferred by the systemic RNAi pathway, in which the limiting step is the cellular import of extracellular RNAs via SID-1. To better understand the physiological role of systemic RNAi in vivo, we modified the function of SID-1 through loss-of-function mutation and tissue-specific overexpression of sid-1 in C. elegans. We observed that sid-1 loss-of-function mutants are as healthy as wild-type worms. Conversely, overexpression of sid-1 in intestine, muscle, or neurons rendered worms short-lived. The effects of intestinal sid-1 overexpression were reversed by silencing the components of the systemic RNAi pathway sid-1, sid-2 and sid-5, thus implicating RNA transport. Moreover, silencing the miRNA biogenesis proteins pash-1 and dcr-1 rendered the lifespan of worms with intestinal sid-1 overexpression similar to controls. Lastly, we observed that the lifespan decrease produced by tissue-specific sid-1 overexpression was dependent on the bacterial food source. Collectively, our data support the notion that systemic RNA signaling is tightly regulated, and unbalancing that process provokes a reduction in lifespan.
k2v: A Containerized Workflow for Creating VCF Files from Kintelligence Targeted Sequencing Data

The ForenSeq Kintelligence kit developed by Verogen is a targeted Illumina sequencing assay that genotypes 10,230 single nucleotide polymorphisms designed for forensic genetic genealogy, forensic DNA phenotyping, and ancestry inference. We developed k2v, a containerized workflow for creating standard specification-compliant variant call format (VCF) files from the custom output data produced by the Kintelligence Universal Analysis Software. VCF files produced with k2v enable the use of many pre-existing, widely used, community-developed tools for manipulating and analyzing genetic data in the standard VCF format. Here we describe the k2v implementation, demonstrate its usage, and use the VCF produced by k2v to demonstrate downstream analyses that can easily be performed with pre-existing tools using VCF data as input: concordance analysis, ancestry inference, and relationship estimation. k2v is distributed as a Docker container available on Docker Hub. Documentation and source code for k2v is freely available under the GNU Public License (GPL-3.0) at https://github.com/signaturescience/k2v.
The Neural Correlates of Arousal: The Ventral Posterolateral Nucleus-Global Transient Co-Activation

Arousal and awareness are two components of consciousness whose the neural mechanisms remain unclear. Spontaneous increases of global (brain-wide) blood-oxygenation-level-dependent (BOLD) signal has been found to be sensitive to changes in arousal. By contrasting BOLD datasets with altered arousal levels, we found that the activation of ventral posterolateral nucleus (VPL) decreased during transient increase in the global signal (top 17% data) in low arousal and awareness states (non-rapid eye movement sleep and anesthesia) as compared to wakefulness, and even in eye-closed (compared with eyes-open) in healthy awake-states, while this activation remained unchanged in patients with unresponsive wakefulness syndrome characterized by high arousal without awareness. These results demonstrate that co-activation of the VPL and global activity is critical to arousal, but not to awareness. One-Sentence Summary The VPL nucleus-global brain transient co-activation is related to physiological arousal but not to perceptual awareness.
Drivers of mangrove vulnerability and resilience to tropical cyclones in the North Atlantic Basin

The North Atlantic Basin (NAB) is seeing a significant increase in the frequency and intensity of tropical cyclones since the 1980s, with record-breaking seasons such as 2017 and 2020. However, little is known about how coastal ecosystems, particularly mangroves in the Gulf of Mexico and the Caribbean, are responding to these new “climate normals” at regional and subregional scales. Wind speed, rainfall, pre-cyclone forest structure, and hydro-geomorphology are known to influence mangrove damage and recovery following cyclones in the NAB. However, these studies have focused on site-specific responses and individual cyclonic events. Here, we analyze 25 years (1996-2020) of mangrove vulnerability (damage after a cyclone) and short-term resilience (recovery after damage) for the entire NAB and its subregions, using multi-annual, remote sensing-derived databases. We applied machine learning to characterize the influence of 22 potential drivers that include previously researched variables and new ones such as human development and long-term climate trends. The characteristics of the cyclones mainly drive vulnerability at the regional level, while resilience is largely driven by site-specific conditions. These include long-term climate conditions, such as air temperature and drought trends, pre-cyclone habitat conditions, such as canopy cover and height and soil organic carbon stock, and human interventions on the land. Rates and drivers of mangrove vulnerability and resilience vary across subregions in the NAB, and hotspots for restoration and conservation actions are highlighted within subregions. The impacts of increasing cyclone activity need to be framed in the context of climate change compound effects and heavy human influences in the region. There is an urgent need to value the restoration and conservation of mangroves as fundamental Nature-based Solutions against cyclone impacts in the NAB.
Terraces in Species Tree Inference from Gene Trees

A terrace in a phylogenetic tree space is a region where all trees contain the same set of subtrees, due to certain patterns of missing data among the taxa sampled, resulting in an identical optimality score for a given data set. This was first investigated in the context of phylogenetic tree estimation from sequence alignments using maximum likelihood (ML) and maximum parsimony (MP). The concept of terraces was later extended to the species tree inference problem from a collection of gene trees, where a set of equally optimal species trees was referred to as a “pseudo” species tree terrace. Pseudo terraces do not consider the topological proximity of the trees in terms of the induced subtrees resulting from certain patterns of missing data. In this study, we mathematically characterize species tree terraces and investigate the mathematical properties and conditions that lead multiple species trees to induce/display an identical set of locus-specific subtrees owing to missing data. We report that species tree terraces are agnostic to gene tree topologies and the discordance therein. Therefore, we introduce and characterize a special type of gene tree topology-aware terrace which we call “peak terrace”, and investigate conditions on the patterns of missing data that give rise to peak terraces. In addition to the theoretical and analytical results, we empirically investigated different challenges as well as various opportunities pertaining to the multiplicity of equally good species trees in terraced landscapes. Based on an extensive experimental study involving both simulated and real biological datasets, we present the prevalence of species tree terraces and the resulting ambiguity created for tree search algorithms. Remarkably, our findings indicate that the identification of terraces and the trees within them can substantially enhance the accuracy of summary methods. Furthermore, we demonstrate that reasonably accurate branch support can be computed by leveraging trees sourced from these terraces.
Neural correlates of probabilistic information processing in gesture-speech integration

How information of different modalities (e.g., speech and gesture) frame into a unified one remains unclear in the neurobiology of language. Leveraging the information-theoretic complexity metrics of entropy and mutual information (MI) to quantify gestures and speech, the present event-related potentials and chronometric double-pulse transcranial magnetic stimulation (TMS) study investigated the neural processes during probabilistic gesture-speech integration. In the early sensory processing stage, we found a positive correlation of P1 amplitude with speech entropy and a negative correlation of N1-P2 amplitude with gesture entropy, while the TMS disruption effect of posterior middle temporal gyrus (pMTG) was negatively correlated with speech entropy. In the lexico-semantic processing stage, we observed a negative correlation of N400 amplitude with both gesture entropy and gesture-speech MI, a negative correlation of late positive component amplitude with speech entropy, together with correlations of the TMS interruption effect of inferior frontal gyrus (IFG) with gesture entropy, speech entropy and their MI. Our findings suggest a probabilistically updated lexical representation that was dynamically framed by top-down gesture constraint, bottom-up speech encoding and their interplay. A 5-step process in the pMTG-IFG-pMTG neural circuit is hypothesized for probabilistic gesture-speech processing, which promises a better understanding of the predictive multisensory language processing.
Quantifying the distribution of feature values over data represented in arbitrary dimensional spaces

Background Identifying the structured distribution (or lack thereof) of a given feature over a point cloud is a general research question. In the neuroscience field, this problem arises while investigating representations over neural manifolds (e.g., spatial coding), in the analysis of neurophysiological signals (e.g., auditory coding) or in anatomical image segmentation. New method We introduce the Structure Index (SI) as a graph-based topological metric to quantify the distribution of feature values projected over data in arbitrary D-dimensional spaces (neurons, time stamps, pixels). The SI is defined from the overlapping distribution of data points sharing similar feature values in a given neighborhood. Results Using model data clouds we show how the SI provides quantification of the degree of local versus global organization of feature distribution. SI can be applied to both scalar and vectorial features permitting quantification of the relative contribution of related variables. When applied to experimental studies of head-direction cells, it is able to retrieve consistent feature structure from both the high- and low-dimensional representations. Finally, we provide two general-purpose examples (sound and image categorization), to illustrate the potential application to arbitrary dimensional spaces. Comparison with existing methods Most methods for quantifying structure depend on cluster analysis, which are suboptimal for continuous features and non-discrete data clouds. SI unbiasedly quantifies structure from continuous data in any dimensional space. Conclusions The method provides versatile applications in the neuroscience and data science fields Highlights The Structure Index is a graph-based topological metric It quantifies the distribution of feature values in arbitrary dimensional spaces It can be applied to both scalar and vectorial features When applied to the head-direction neural system, it extracts concordant information from high- and low-dimensional representations It can be extended to sound and image categorization, expanding the range of applications
GX 339-4 - Black hole or neutron star X-ray binary

Optical spectra of the highly variable X-ray source GX 339-4 show an emission-line spectrum characteristic of an accretion disk. Velocity variations suggest the orbital period lies between 0.2 and 2 days. Periods in this range limit the mass of the compact star to less than 2.5 solar mass. The distance estimated from the interstellar lines and the color is about 4 kpc. At this distance the velocity expected from galactic rotation differs by over 100 km/s from the observed systemic velocity. 19 references.
Analytic solution for grand confluent hypergeometric function

In previous paper I construct an approximative solution of the power series expansion in closed forms of Grand Confluent Hypergeometric (GCH) function only up to one term of A_n's [4]. And I obtain normalized constant and orthogonal relation of GCH function. In this paper I will apply three term recurrence formula [3] to the power series expansion in closed forms of GCH function (infinite series and polynomial) including all higher terms of A_n's. In general most of well-known special function with two recursive coefficients only has one eigenvalue for the polynomial case. However this new function with three recursive coefficients has infinite eigenvalues that make B_n's term terminated at specific value of index n because of three term recurrence formula [3]. This paper is 9th out of 10 in series "Special functions and three term recurrence formula (3TRF)". See section 6 for all the papers in the series. Previous paper in series deals with generating functions of Lame polynomial in the Weierstrass's form [28]. The next paper in the series describes the integral formalism and the generating function of GCH function [30].
Encorafenib Acts as a Dual-Activity Chemosensitizer through Its Inhibitory Effect on ABCC1 Transporter In Vitro and Ex Vivo

Encorafenib (LGX818, trade name Braftovi), a novel BRAF inhibitor, has been approved for the treatment of melanoma and colorectal cancer. In the present work, we evaluated encorafenib’s possible antagonistic effects on the pharmacokinetic mechanisms of multidrug resistance (MDR), as well as its perpetrator role in drug interactions. Firstly, encorafenib potently inhibited the efflux function of the ABCC1 transporter in drug accumulation assays, while moderate and null interaction levels were recorded for ABCB1 and ABCG2, respectively. In contrast, the mRNA expression levels of all the tested transporters were not altered by encorafenib. In the drug combination studies, we found that daunorubicin and topotecan resistances were synergistically attenuated by the encorafenib-mediated interaction in A431-ABCC1 cells. Notably, further experiments in ex vivo patient-derived explants confirmed the MDR-modulating ability of encorafenib. Advantageously, the overexpression of tested drug efflux transporters failed to hinder the antiproliferative activity of encorafenib. In addition, no significant modulation of the CYP3A4 enzyme’s activity by encorafenib was observed. In conclusion, our work indicated that encorafenib can act as an effective chemosensitizer targeting the ABCC1-induced MDR. Our in vitro and ex vivo data might provide valuable information for designing the novel effective scheme applicable in the clinical pharmacotherapy of BRAF-mutated/ABCC1-expressing tumors.
Detection of Security Attacks Using Time Series Analysis

There are an increasing number of connected devices due to the evolution of the IoT. With this evolution, the Internet is now more exposed to security attacks. One of the ways to detect an attack is by analyzing the trafﬁc, trying to distinguish regular trafﬁc from the outliers caused by the attacks. This Msc Dissertation studies methods for detecting security attacks in time series based on a dataset to which the methods will be applied and analyse some algoritms to understand which is the best one for the dataset under study. After the dataset is introduced, an analysis of the performance of the algorithms is carried out by varying their parameters. Among the studied methods are an heuristic, Tukey’s method, Distance Based-Outlier, SAX, and Tukey’s method combined with PAA. Our results indicate that the latter method outperforms the remaining one for the detection of redirection attacks caused by BGP preﬁx hijacking.