Miracle-dz/UniFAR-FTUs huggingface dataset:
A circulating biomarker of facioscapulohumeral muscular dystrophy clinical severity, valid in skeletal muscle and blood

Facioscapulohumeral muscular dystrophy (FSHD) is incurable. DUX4 mis-expression is believed to underlie FSHD pathogenesis, alongside PAX7 target gene repression, yet clinical trials lack robust biomarkers of severity. FSHD entails fatty replacement of muscle, accelerated by inflammation, we thus performed RNA-sequencing on both an MRI guided inflamed (TIRM+) and non-inflamed (TIRM-) muscle biopsies from clinically-characterised FSHD patients, alongside peripheral blood mononucleated cells (PBMCs). PAX7 target gene repression in TIRM-muscle associates with severity. DUX4 target gene biomarkers associate with lower limb fat fraction and D4Z4 repeat length, but not severity. PAX7 target gene repression in muscle correlates with levels in matched PBMCs. A refined biomarker computed in PBMCs associates with severity in FSHD patients, and also validates as a classifier of severity in an independent set of 54 FSHD patient blood samples. In summary, we present a minimally-invasive, circulating, transcriptomic biomarker of FSHD clinical severity valid in muscle and blood.
A cryogenic, coincident fluorescence, electron, and ion beam microscope

Cryogenic electron tomography (cryo-ET) combined with sub-tomogram averaging, allows in-situ visualisation and structure determination of macromolecular complexes at sub-nanometre resolution. Cryogenic focused ion beam (cryo-FIB) micromachining is used to prepare a thin lamella-shaped sample out of a frozen-hydrated cell for cryo-ET imaging, but standard cryo-FIB fabrication is blind to the precise location of the structure or proteins of interest. Fluorescence-guided focused ion beam (FIB) milling at target locations requires multiple sample transfers prone to contamination, and relocation and registration accuracy is often insufficient for 3D targeting. Here, we present in-situ fluoresence microscopy-guided FIB fabrication of a frozen-hydrated lamella to solve this problem: we built a coincident 3-beam cryogenic correlative microscope by retrofitting a compact cryogenic microcooler, custom positioning stage, and an inverted widefield fluorescence microscope (FM) on an existing focused ion-beam scanning electron microscope (FIB-SEM). We show FM controlled targeting at every milling step in the lamella fabrication process, validated with transmission electron microscope (TEM) tomogram reconstructions of the target regions. The ability to check the lamella during and after the milling process results in a higher success rate in the fabrication process and will increase the throughput of fabrication for lamellae suitable for high-resolution imaging.
SpaCeNet: Spatial Cellular Networks from omics data

Advances in omics technologies have allowed spatially resolved molecular profiling of single cells, providing a window not only into the diversity and distribution of cell types within a tissue, but also into the effects of interactions between cells in shaping the transcriptional landscape. Cells send chemical and mechanical signals which are received by other cells, where they can subsequently initiate context-specific gene regulatory responses. These interactions and their responses shape the individual molecular phenotype of a cell in a given microenvironment. RNAs or proteins measured in individual cells together with the cells’ spatial distribution provide invaluable information about these mechanisms and the regulation of genes beyond processes occurring independently in each individual cell. “SpaCeNet” is a method designed to elucidate both the intracellular molecular networks (how molecular variables affect each other within the cell) and the intercellular molecular networks (how cells affect molecular variables in their neighbors). This is achieved by estimating conditional independence relations between captured variables within individual cells and by disentangling these from conditional independence relations between variables of different cells. A python implementation of SpaCeNet is publicly available at https://github.com/sschrod/SpaCeNet.
Characterization of b-value dependent T2 relaxation rates for probing neurite microstructure

Brain tissue microstructure is characterized by heterogeneous diffusivity and transversal relaxation rates. Standard diffusion MRI (dMRI) is acquired using a single echo time (TE) and only provides information about heterogeneous diffusivity in the underlying tissue. Combined relaxation diffusion MRI (rdMR) integrates dMRI with multiple TEs to probe the coupling between relaxation rate and diffusivity. This work introduces a method to model rdMRI data signals by characterizing the apparent relaxation rate related to dMRI with different b-values. The proposed approach can extrapolate dMRI signals to ultra-long or ultra-short TEs to increase or reduce signals from intra-neurite water to improve the characterization of neurite microstructure without solving multi-compartment models. The performance of the proposed method was examined using an in vivo dataset acquired from a clinical scanner to estimate neurite sizes.
Random and natural non-coding RNA have similar structural motif patterns but can be distinguished by bulge, loop, and bond counts

An important question in evolutionary biology is whether and in what ways genotype-phenotype (GP) map biases can influence evolutionary trajectories. Untangling the relative roles of natural selection and biases (and other factors) in shaping phenotypes can be difficult. Because RNA secondary structure (SS) can be analysed in detail mathematically and computationally, is biologically relevant, and a wealth of bioinformatic data is available, it offers a good model system for studying the role of bias. For quite short RNA (length L ≤ 126), it has recently been shown that natural and random RNA are structurally very similar, suggesting that bias strongly constrains evolutionary dynamics. Here we extend these results with emphasis on much larger RNA with length up to 3000 nucleotides. By examining both abstract shapes and structural motif frequencies (ie the numbers of helices, bonds, bulges, junctions, and loops), we find that large natural and random structures are also very similar, especially when contrasted to typical structures sampled from the space of all possible RNA structures. Our motif frequency study yields another result, that the frequencies of different motifs can be used in machine learning algorithms to classify random and natural RNA with quite high accuracy, especially for longer RNA (eg ROC AUC 0.86 for L = 1000). The most important motifs for classification are found to be the number of bulges, loops, and bonds. This finding may be useful in using SS to detect candidates for functional RNA within ‘junk’ DNA regions.
Altered visual cortex excitability in premenstrual dysphoric disorder: Evidence from magnetoencephalographic gamma oscillations and perceptual suppression

Premenstrual dysphoric disorder (PMDD) is a psychiatric condition characterized by extreme mood shifts, anxiety, and irritability during the premenstrual period. Abnormal sensitivity to allopregnanolone, a neurosteroid that normally potentiates inhibition, and an increased ratio of neural excitation-to-inhibition (E/I) have been linked to the pathophysiology of PMDD. We hypothesized that in subjects with PMDD these factors will lead to an altered frequency of magnetoencephalographic (MEG) visual gamma oscillations, altered modulation of their power by the strength of excitatory drive and to an altered perceptual spatial suppression. We examined women with PMDD and age-matched control women twice: during the asymptomatic follicular and symptomatic luteal phases of the menstrual cycle (MC). MEG gamma oscillations were recorded while modulating excitatory drive to the visual cortex by increasing drift rate of high-contrast visual gratings. Perceptual suppression was assessed as a degree of impairment of the discrimination of visual motion direction with increasing stimulus size. In women with PMDD, the gamma response (GR) peak frequency and its modulation by the drift rate were normal, whereas modulation of the GR power was significantly altered. A moderate increase in drift rate had an unusually strong facilitating effect on the GR power in PMDD, regardless of the MC phase. In contrast, the effect of increasing drift rate, which normally suppresses GR power, was attenuated in PMDD in the luteal phase and predicted symptom severity estimated on the same day. Perceptual spatial suppression did not differ between the groups, but decreased from the follicular to the luteal phase only in PMDD subjects. The atypical GR power modulation suggests that neuronal excitability in the visual cortex is constitutively elevated in women with PMDD, and that their E/I ratio is additionally shifted toward excitation during the luteal phase, possibly due to an abnormal sensitivity to neurosteroids. However, the unchanged frequency of GR and normal spatial suppression in women with PMDD speak against the dysfunction of their inhibitory neurons, at least those involved in generation of visual gamma oscillations. Three key points Atypical modulation of visual gamma power by excitatory drive in women with PMDD suggests the presence of neuronal hyperexcitability, which is exacerbated during the symptomatic luteal phase, possibly due to altered sensitivity to neurosteroids. The peak frequency of gamma oscillations does not differ between women with PMDD and control women and demonstrates the luteal phase-specific effect of the 1st scan in both groups, which suggest normal functioning of inhibitory neurons in the visual cortex in PMDD. The presence of normal perceptual spatial suppression also speaks against inhibitory deficit in the visual cortex in PMDD.
Diversity and Ecology of Caudoviricetes Phages with Genome Terminal Repeats in Fecal Metagenomes from Four Dutch Cohorts

The human gut harbors numerous viruses infecting the human host, microbes and other inhabitants of the gastrointestinal tract. Most of these viruses remain undiscovered, and their influence on human health is unknown. Here we characterize viral genomes in gut metagenomic data from 1,950 individuals from four population and patient cohorts. We focus on a subset of viruses that is highly abundant in the gut, remains largely uncharacterized, and allows confident complete genome identification – phages that belong to the class Caudoviricetes and possess genome terminal repeats. We detect 1,899 species-level units belonging to this subset, 19% of which do not have complete representative genomes in major public gut virome databases. These units display diverse genomic features, are predicted to infect a wide range of microbial hosts, and on average account for < 1% of metagenomic reads. Analysis of longitudinal data from 338 individuals shows that the composition of this fraction of the virome remained relatively stable over a period of 4 years. We also demonstrate that 54 species-level units are highly prevalent (detected in > 5% of individuals in a cohort). Finally, we find 34 associations between highly prevalent phages and human phenotypes, 24 of which can be explained by the relative abundance of potential hosts.
Modular Streaming Pipeline of Eye/Head Tracking Data Using Tobii Pro Glasses 3

Head-mounted tools for eye/head tracking are increasingly used for assessment of visual behavior in navigation, sports, sociology, and neuroeconomics. Here we introduce an open-source python software (TP3Py) for collection and analysis of portable eye/head tracking signals using Tobii Pro Glasses 3. TP3Py’s modular pipeline provides a platform for incorporating user-oriented functionalities and comprehensive data acquisition to accelerate the development in behavioral and tracking research. Tobii Pro Glasses 3 is equipped with embedded cameras viewing the visual scene and the eyes, inertial measurement unit (IMU) sensors, and video-based eye tracker implemented in the accompanying unit. The program establishes a wireless connection to the glasses and, within separate threads, continuously leverages the received data in numerical or string formats accessible for saving, processing, and graphical purposes. Built-in modules for presenting eye, scene, and IMU data to the experimenter have been adapted as well as communicating modules for sending the raw signals to stimulus/task controllers in live fashion. Closed-loop experimental designs are limited due to the 140ms time delay of the system, but this limitation is compensated by the portability of the eye/head tracking. An offline data viewer has been also incorporated to allow more time-consuming computations. Lastly, we demonstrate example recordings involving vestibulo-ocular reflexes, saccadic eye movements, optokinetic responses, or vergence eye movements to highlight the program’s measurement capabilities to address various experimental goals. TP3Py has been tested on Windows with Intel processors, and Ubuntu operating systems with Intel or ARM (Raspberry Pie) architectures.
From Gradient to Sectioning in CUBE: Workflow for Generating and Imaging Organoid with Localized Differentiation

Advancements in organoid culture methods have led to a widespread availability of various in vitro mini-organs that mimic native tissues in many ways. Yet, the bottleneck remains to generate complex organoids with body axis patterning, as well as keeping the orientation of organoid samples during post-experiment analysis processes. In this paper, we present a workflow for culturing organoids with gradient using a previously developed CUBE culture device, then sectioning samples with the CUBE to retain information on the gradient direction of the sample. We show that hiPSC spheroids cultured with separate differentiation media on two opposing ends of the CUBE resulted in localized expressions of the respective differentiation markers, in contrast to homogeneous distribution of markers in controls with the same media on both ends. We also describe the processes for cryo and paraffin sectioning of gradient-cultured spheroids in CUBE to retain gradient orientation information. This workflow from gradient culture to sectioning with CUBE can provide researchers with a convenient tool to generate increasingly complex organoids and study their developmental processes in vitro.
Cell cycle progression defects and impaired DNA damage signaling drive enlarged cells into senescence

Cellular senescence plays an important role in development, ageing, and cancer biology. Senescence is associated with increased cell size, but how this contributes to permanent cell cycle exit is poorly understood. Using reversible G1 cell cycle arrests combined with growth rate modulation, we examined the effects of excess cell size on cell cycle progression in human cells. We show that enlarged cells paradoxically have high levels of G1/S regulators relative to cells that were maintained at physiological size but also induce p21, which restrains cell cycle entry and protects against cell division failure. Furthermore, we find that enlarged cells bear an increased propensity for DNA breakage and concomitant DNA damage repair defects that are established during G1. Based on these observations, we propose that impaired DNA damage repair pathways prime enlarged cells for persistent replication-acquired damage, ultimately leading to catastrophic cell cycle failure and permanent cell cycle exit.
Neural adaptation and fractional dynamics as a window to underlying neural excitability

The relationship between macroscale electrophysiological recordings and the dynamics of underlying neural activity remains unclear. We have previously shown that low frequency EEG activity (<1 Hz) is decreased at the seizure onset zone (SOZ), while higher frequency activity (1-50 Hz) is increased. These changes result in power spectral densities (PSDs) with flattened slopes near the SOZ, which are assumed to be areas of increased excitability. We wanted to understand possible mechanisms underlying PSD changes in brain regions of increased excitability. We hypothesize that these observations are consistent with changes in adaptation within the neural circuit. We developed a theoretical framework and tested the effect of adaptation mechanisms, such as spike frequency adaptation and synaptic depression, on excitability and PSDs using filter-based neural mass models and conductance-based models. We compared the contribution of single timescale adaptation and multiple timescale adaptation. We found that adaptation with multiple timescales alters the PSDs. Multiple timescales of adaptation can approximate fractional dynamics, a form of calculus related to power laws, history dependence, and non-integer order derivatives. Coupled with input changes, these dynamics changed circuit responses in unexpected ways. Increased input without synaptic depression increases broadband power. However, increased input with synaptic depression may decrease power. The effects of adaptation were most pronounced for low frequency activity (< 1Hz). Increased input combined with a loss of adaptation yielded reduced low frequency activity and increased higher frequency activity, consistent with clinical EEG observations from SOZs. Spike frequency adaptation and synaptic depression, two forms of multiple timescale adaptation, affect low frequency EEG and the slope of PSDs. These neural mechanisms may underlie changes in EEG activity near the SOZ and relate to neural hyperexcitability. Neural adaptation may be evident in macroscale electrophysiological recordings and provide a window to understanding neural circuit excitability. Author Summary Electrophysiological recordings such as EEG from the human brain often come from many thousands of neurons or more. It can be difficult to relate recorded activity to characteristics of the underlying neurons and neural circuits. Here, we use novel theoretical framework and computational neural models to understand how neural adaptation might be evident in human EEG recordings. Neural adaptation includes mechanisms such as spike frequency adaptation and short-term depression that emphasize stimulus changes and help promote stability. Our results suggest that changes in neural adaptation affect EEG signals, especially at low frequencies. Further, adaptation can lead to changes related to fractional derivatives, a kind of calculus with non-integer orders. Neural adaptation may provide a window into understanding specific aspects of neuron excitability even from EEG recordings.
Differential gene expression analysis and physiological response characteristics of passion fruit (Passiflora edulis) buds under high-temperature stress

High temperature in summer is an unfavorable factor for passion fruit (Passiflora edulis), which can lead to restricted growth, short flowering period, few flower buds, low fruit setting rate, severe fruit drop, and more deformed fruit. To explore the molecular physiology mechanism of passion fruit responding to high-temperature stress, we use ‘Zhuangxiang Mibao’, a hybrid passion fruit cultivar, as the test material. Several physiological indicators were measured and compared between high-temperature (average temperature 38°C) and nonmoral temperature (average temperature 25°C) conditions, including photosynthesis, chlorophyll fluorescence parameters, POD, SOD activity and malondialdehyde content. We performed RNA-seq analysis combined with biochemistry experiment to investigate the gene and molecular pathways that respond to high-temperature stress. The results showed that some physiological indicators in the high-temperature group, including the net photosynthetic rate, stomatal conductance, intercellular CO2 concentration, transpiration rate, and the maximum chemical quantum yield of PS∥, were significantly lower than those of the control group. Malondialdehyde content was substantially higher than the control group, while superoxide dismutase and superoxide dismutase activities decreased to different degrees. Transcriptome sequencing analysis showed that 140 genes were up-regulated and 75 genes were down-regulated under high-temperature stress. GO and KEGG annotation analysis of differentially expressed genes revealed many metabolic pathways related to high-temperature stress. Further investigation revealed that 30 genes might be related to high-temperature stress, such as CAO, GSH, WRKY, and HSP, which have also been reported in other species. The results of real-time fluorescence quantitative PCR and RNA-seq of randomly selected ten genes are consistent, which suggests that the transcriptome sequencing results were reliable. Our study provides a theoretical basis for the mechanism of passion fruit response to high-temperature stress. Also, it gives a theoretical basis for the subsequent breeding of new heat-resistant passion fruit varieties.
Drug-Drug Interaction Extraction from Biomedical Text using Relation BioBERT with BLSTM

Drug-drug interactions (DDIs) happen when two or more drugs interact. DDIs may change the effect of drugs in the body which can induce adverse effects and severe diseases for patients. As a result, detecting the interaction between drugs is essential. In the last years, many new DDIs have been found and added to the medical datasets with the rise in the number of discovered drugs. On the other hand, since a lot of this information is still in Biomedical articles and sources, there is a need for a method to extract DDIs information. However, despite the development of many techniques, attaining good prediction accuracy is the main issue. This paper proposes a deep learning approach that: 1) uses the power of Relation BioBERT (R-BioBERT) to detect and classify the DDIs and 2) employs the Bidirectional Long-Short Term Memory (BLSTM) to further increase the prediction quality. Not only does this paper study whether the two drugs have an interaction or not, but it also studies specific types of interactions between drugs. The paper also provides that using BLSTM can significantly increase the F-scores compared to the baseline model on the famous SemEval 2013, TAC 2018, and TAC 2019 DDI Extraction datasets.
Real time visualisation of conjugation reveals the molecular strategy evolved by the conjugative F plasmid to ensure the sequential production of plasmid factors during establishment in the new host cell

DNA conjugation is a contact-dependent horizontal gene transfer mechanism responsible for disseminating drug resistance among bacterial species. Conjugation remains poorly characterised at the cellular scale, particularly regarding the reactions occurring after the plasmid enters the new host cell. Here, we use live-cell microscopy to visualise the intracellular dynamics of conjugation in real time. We reveal that the transfer of the plasmid in single-stranded DNA (ssDNA) form followed by its conversion into double-stranded DNA (dsDNA) are fast and efficient processes that occur with specific timing and subcellular localisation. Notably, the ss-to-dsDNA conversion is the critical step that governs the timing of plasmid-encoded protein production. The leading region that first enters the recipient cell carries single-stranded promoters that allow the early and transient synthesis of leading proteins immediately upon entry of the ssDNA plasmid. The subsequent ss-to-dsDNA conversion turns off leading gene expression and licences the expression of the other plasmid genes under the control of conventional double-stranded promoters. This elegant molecular strategy evolved by the conjugative plasmid allows for the timely production of factors sequentially involved in establishing, maintaining and disseminating the plasmid.