Miracle-dz/UniFAR-FTUs huggingface dataset:
GENIUS: GEnome traNsformatIon and spatial representation of mUltiomicS data

The application of next-generation sequencing (NGS) has transformed cancer research. As costs have decreased, NGS has increasingly been applied to generate multiple layers of molecular data from the same samples, covering genomics, transcriptomics, and methylomics. Integrating these types of multi-omics data in a combined analysis is now becoming a common issue with no obvious solution, often handled on an ad-hoc basis, with multi-omics data arriving in a tabular format and analyzed using computationally intensive statistical methods. These methods particularly ignore the spatial orientation of the genome and often apply stringent p-value corrections that likely result in the loss of true positive associations. Here, we present GENIUS (GEnome traNsformatIon and spatial representation of mUltiomicS data), a framework for integrating multi-omics data using deep learning models developed for advanced image analysis. The GENIUS framework is able to transform multi-omics data into images with genes displayed as spatially connected pixels and successfully extract relevant information with respect to the desired output. Here, we demonstrate the utility of GENIUS by applying the framework to multi-omics datasets from the Cancer Genome Atlas. Our results are focused on predicting the development of metastatic cancer from primary tumors, and demonstrate how through model inference, we are able to extract the genes which are driving the model prediction and likely associated with metastatic disease progression. We anticipate our framework to be a starting point and strong proof of concept for multi-omics data transformation and analysis without the need for statistical correction.
The critical role of Dmnt1 during spermatogenesis is not predictable, but knockdown does cause pervasive differential transcription

Cytosine methylation and its machinery influence the gene expression of many eukaryotes; however, insects are an exception to this general tenet despite many lineages retaining methyltransferases and methylated genomes. Here, we tested the a priori hypothesis that perturbed genetic pathways will be associated with meiosis using transcriptomics because previous our work using Oncopeltus fasciatus shows that gametogenesis is interrupted at meiosis following knockdown of DNA methyltransferase 1 (Dnmt1). Testes, which are almost exclusively contain gametes at varying stages of development, were sampled at 7-days and 14-days following knockdown of Dmnt1 using RNAi. Using microscopy, we found actively dividing spermatocysts were reduced at both sampling points. However, we found limited support of perturbation for our predicted cell cycle and meiotic pathways and only at 14-days. We found that Gene Ontology terms had no preferential enrichment for meiosis-associated genes. Following our a priori tests, we used the full dataset to uncover further candidate pathways influenced by Dnmt1 knockdown. Very few genes were differentially expressed at 7-days, but nearly half were at 14-days. We did not find strong candidate pathways for how Dnmt1 knockdown was achieving its effect through Gene Ontology term overrepresentation analysis. Given the evidence from microscopy, we propose Dnmt1 knockdown results in condensed nuclei after mitosis-meiosis transition and then cellular arrest. This explanation posits that differential gene expression is a product of comparing healthy to arrested cells and is not a targeted response.
Evaluating the Performance of Widely Used Phylogenetic Models 1 for Gene Expression Evolution 2

13 Phylogenetic comparative methods allow biologists to make inferences about the 14 evolutionary history of phenotypes. These methods are increasingly used to study the 15 evolution of gene expression. However, it is unknown whether the distributional 16 assumptions of phylogenetic models designed for quantitative phenotypic traits are 17 realistic for expression data (i.e., how well do the models actually perform? ); and the 18 reliability of conclusions of phylogenetic comparative studies of gene expression may 19 depend on whether the data is well-described by the chosen model. To evaluate this, we 20 first fit several phylogenetic models of trait evolution to 9 previously published 21 comparative expression datasets, comprising a total of 54,774 genes with 155,679 unique 22 gene-tissue combinations. Using a previously developed approach, we then assessed how 23 well the best model of the set described the data in an absolute (not just relative) sense. 24 First, we find that Ornstein-Uhlenbeck models were the preferred model for 59.8% of 25 gene-tissue combinations. Second, we find that for 39% of gene-tissue combinations, the 26 best fit model was found to perform poorly by at least one of the test statistics we 27 examined. Third, we find that when simple models do not perform well, this appears to 28 be typically a consequence of failing to fully account for heterogeneity in the rate of the 29 evolution of gene expression across lineages. We advocate that assessment of model 30 performance should become a routine component of phylogenetic comparative 31 expression studies; doing so can improve the reliability of inferences and inspire the 32 development of novel models. 33
Conserved Chamber-Specific Polyploidy Maintains Heart Function in Drosophila

Developmentally programmed polyploidy (whole-genome-duplication) of cardiomyocytes is common across evolution. Functions of such polyploidy are essentially unknown. Here, we reveal roles for precise polyploidy levels in cardiac tissue. We highlight a conserved asymmetry in polyploidy level between cardiac chambers in Drosophila larvae and humans. In Drosophila, differential Insulin Receptor (InR) sensitivity leads the heart chamber to reach a higher ploidy/cell size relative to the aorta chamber. Cardiac ploidy-reduced animals exhibit reduced heart chamber size, stroke volume, cardiac output, and acceleration of circulating hemocytes. These Drosophila phenotypes mimic systemic human heart failure. Using human donor hearts, we reveal asymmetry in nuclear volume (ploidy) and insulin signaling between the left ventricle and atrium. Our results identify productive and likely conserved roles for polyploidy in cardiac chambers and suggest precise ploidy levels sculpt many developing tissues. These findings of productive cardiomyocyte polyploidy impact efforts to block developmental polyploidy to improve heart injury recovery.
Condensate formation of the human RNA-binding protein SMAUG1 is controlled by its intrinsically disordered regions and interactions with 14-3-3 proteins

SMAUG1 is a human RNA-binding protein that is known to be dysregulated in a wide range of diseases. It is evolutionarily conserved and has been shown to form condensates containing translationally repressed RNAs. This indicates that condensation is central to proper SMAUG1 function; however, the factors governing condensation are largely unknown. In this work, we show that SMAUG1 drives the formation of liquid-like condensates in cells through its non-conventional C-terminal prion-like disordered region. We use biochemical assays to show that this liquid-liquid phase separation is independent of RNA binding and does not depend on other large, disordered regions that potentially harbor several binding sites for partner proteins. Using a combination of computational predictions, structural modeling, in vitro and in cell measurements, we also show that SMAUG1-driven condensation is negatively regulated by direct interactions with members of the 14-3-3 protein family. These interactions are mediated by four distinct phospho-regulated short linear motifs embedded in the disordered regions of SMAUG1, working synergistically. Interactions between SMAUG1 and 14-3-3 proteins drive the dissolution of condensates, alter the dynamics of the condensed state, and are likely to be intertwined with currently unknown regulatory mechanisms. Our results provide information on how SMAUG1 phase separation is regulated and the first known instance of 14-3-3 proteins being able to completely dissolve condensates by directly interacting with a phase separation driver, which might be a general mechanism in cells to regulate biological condensation. Graphical abstract Highlights SMAUG1 is a human RNA-binding protein capable of condensation with unknown regulation A prion-like domain of SMAUG1 drives condensation via liquid-liquid phase separation SMAUG1 interacts with 14-3-3 proteins via four phospho-regulated short linear motifs 14-3-3 interactions change the dynamics of SMAUG1 condensates, promoting their dissolution This is the first described regulatory mechanism for SMAUG1-driven condensation
Thrombin activation of the factor XI dimer is a multi-staged process for each subunit

Factor XI (FXI), a protein in the intrinsic coagulation pathway, can be activated by two enzymes. In hemostasis, FXI is activated by thrombin, while FXIIa-mediated activation is prothrombotic. The interactions between FXI and its activating enzymes are poorly understood due to their transient nature. Here, we applied structural proteomics, molecular dynamics simulations and binding assays to investigate the interface between thrombin and FXI including the dynamics underlying FXI activation. We demonstrate that activation of FXI is a multi-staged process, where thrombin first binds to Pro520 on FXI, after which it migrates towards the activation site by engaging the apple 1 domain and finally Arg378. We validated with known mutation sites and additionally found that Pro520 is conserved in prekallikrein (PK). This enables binding of thrombin even though it cannot activate PK. Understanding the exact binding of thrombin to FXI points a way for future interventions for bleeding or thrombosis.
Diffsig: Associating Risk Factors With Mutational Signatures

Somatic mutational signatures elucidate molecular vulnerabilities to therapy and therefore detecting signatures and classifying tumors with respect to signatures has clinical value. However, identifying the etiology of the mutational signatures remains a statistical challenge, with both small sample sizes and high variability in classification algorithms posing barriers. As a result, few signatures have been strongly linked to particular risk factors. Here we present Diffsig, a model and R package for estimating the association of risk factors with mutational signatures, suggesting etiologies for the pre-defined mutational signatures. Diffsig is a Bayesian Dirichlet-multinomial hierarchical model that allows testing of any type of risk factor while taking into account the uncertainty associated with samples with a low number of observations. In simulation, we found that our method can accurately estimate risk factor-mutational signal associations. We applied Diffsig to breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development. Diffsig is implemented as an R package available at: https://github.com/jennprk/diffsig.
Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity

Information flow in brain networks is reflected in intracerebral local field potential (LFP) measurements that have both periodic and aperiodic components. The 1/fχ broadband aperiodic component of the power spectra has been shown to track arousal level and to correlate with other physiological and pathophysiological states, with consistent patterns across cortical regions. Previous studies have focused almost exclusively on cortical neurophysiology. Here we explored the aperiodic activity of subcortical nuclei from the human thalamus and basal ganglia, in relation to simultaneously recorded cortical activity. We elaborated on the FOOOF (fitting of one over f) method by creating a new parameterization of the aperiodic component with independent and more easily interpretable parameters, which allows seamlessly fitting spectra with and without an aperiodic knee, a component of the signal that reflects the dominant timescale of aperiodic fluctuations. First, we found that the aperiodic exponent from sensorimotor cortex in Parkinson’s disease (PD) patients correlated with disease severity. Second, although the aperiodic knee frequency changed across cortical regions as previously reported, no aperiodic knee was detected from subcortical regions across movement disorders patients, including the ventral thalamus (VIM), globus pallidus internus (GPi) and subthalamic nucleus (STN). All subcortical region studied exhibited a relatively low aperiodic exponent (χSTN=1.3±0.2, χVIM=1.4±0.1, χGPi=1.4±0.1) that differed markedly from cortical values (χCortex=3.2±0.4, fkCortex=17±5 Hz). These differences were replicated in a second dataset from epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences between subcortical nuclei and the cortex. Significance Statement The broadband aperiodic component of local field potentials is a useful and reproducible index of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters, with which we fit cortical, basal ganglia and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinson’s disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the broadband aperiodic components of basal ganglia and thalamic signals compared to those from neocortex, suggesting that the aperiodic neural timescale of subcortical LFPs is slower than that in cortex.
Exploring the consequences of redirecting an exocytic Rab onto endocytic vesicles

Bidirectional vesicular traffic links compartments along the exocytic and endocytic pathways. Rab GTPases have been implicated in specifying the direction of vesicular transport because anterograde vesicles are marked with a different Rab than retrograde vesicles. To explore this proposal, we sought to redirect an exocytic Rab, Sec4, onto endocytic vesicles by fusing the catalytic domain of the Sec4 GEF, Sec2, onto the CUE localization domain of Vps9, a GEF for the endocytic Rab, Ypt51. The Sec2GEF-GFP-CUE construct was found to localize to bright puncta predominantly near sites of polarized growth and this localization was strongly dependent upon the ability of the CUE domain to bind to the ubiquitin moieties added to the cytoplasmic tails of proteins destined for endocytic internalization. Sec4 and Sec4 effectors were recruited to these puncta with varying efficiency. The puncta appeared to consist of clusters of 80 nm vesicles and although the puncta are largely static, FRAP analysis suggests that traffic into and out of these clusters continues. Cells expressing Sec2GEF-GFP-CUE grew surprisingly well and secreted protein at near normal efficiency, implying that Golgi derived secretory vesicles were delivered to polarized sites of cell growth, where they tethered and fused with the plasma membrane despite the misdirection of Sec4 and its effectors. In total, the results suggest that while Rabs play a critical role in regulating vesicular transport, cells are remarkably tolerant of Rab misdirection.
The Burden of Reliability: How Measurement Noise Limits Brain-Behaviour Predictions

Major efforts in human neuroimaging strive to understand individual differences and find biomarkers for clinical applications by predicting behavioural phenotypes from brain imaging data. An essential prerequisite for identifying generalizable and replicable brain-behaviour prediction models is sufficient measurement reliability. However, the selection of prediction targets is predominantly guided by scientific interest or data availability rather than reliability considerations. Here we demonstrate the impact of low phenotypic reliability on out-of-sample prediction performance. Using simulated and empirical data from the Human Connectome Projects, we found that reliability levels common across many phenotypes can markedly limit the ability to link brain and behaviour. Next, using 5000 subjects from the UK Biobank, we show that only highly reliable data can fully benefit from increasing sample sizes from hundreds to thousands of participants. Overall, our findings highlight the importance of measurement reliability for identifying brain–behaviour associations from individual differences.
Strong and osteoconductive poly(lactic acid) biocomposites by high-shear liquid dispersion of hydroxyapatite nanowhiskers

Abstract Controlled incorporation of bioactive hydroxyapatite (HA) into poly(lactic acid) (PLA) signifies a promising approach to design and development of biomedical-adaptive materials. Here we unravel a microwave-assisted biomineralization approach to synthesis of HA nanowhiskers (HANWs), which were characterized by well-controlled diameter (∼30 nm) and length (80 − 120 nm), combined with a desirable calcium − phosphorus ratio (Ca/P) of 1.67. A high-shear liquid dispersion (HSLD) method that provided a combination of high pressure (up to 50 kPa) and high shear rate approaching 10000 s −1 was established to fabricate homogeneous PLA/HANWs composites. In particular, upon incorporation of 30 wt % HANWs the tensile strength and elastic modulus of PLA-HA30 (76.7 MPa and 3.3 GPa) were elevated by 48% and 84% compared to those of pure PLA, respectively, as accompanied by a nearly 2-fold increase in the cell viability. This work paves a facile yet effective roadway to strong and osteoconductive PLA composites appealing for bone tissue repairing. Graphical Abstract Synopsis: Biomineralization concepts are abstracted to synthesize well-defined and bioactive HANWs, which could be uniformly dispersed in PLA biofilms by high-shear liquid exfoliation.
A Study of the TOMM and DCT in Chinese-Speaking Immigrants with Limited English Proficiency in the United States

Abstract The accuracy of performance validity tests (PVTs) with culturally diverse populations has increasingly been questioned. High false positive rates have been found in some PVTs in culturally and linguistically diverse individuals within the U.S. and internationally. No study to date has investigated the accuracy of PVTs with Chinese-speaking immigrants (CSI) in the U.S. The current study aimed to evaluate two PVTs, the Test of Memory Malingering (TOMM) and Dot Counting Test (DCT), to determine their accuracy in a community sample of CSI with limited English proficiency. These two measures were used in a simulation design, contrasting 52 participants who were instructed to respond honestly to 22 participants instructed to feign incompetency to stand trial. Results demonstrated the scores of TOMM Trial 1 and Trial 2 were effective in classifying honest responders from simulators, whereas the DCT E-score did not differentiate the groups better than chance. However, false positive rates for the TOMM Trial 1, Trial 2, and the DCT E-score were relatively low. Only one honest responder (1.9%) was classified as exerting insufficient effort in TOMM Trial 1 and DCT E-score, and the TOMM Trial 2 did not misclassify any honest responders. Implications and cautionary statements are provided and discussed.
Using finite element method for the determination of elastic moduli by resonant ultrasound spectroscopy

Resonant ultrasound spectroscopy is a recent experimental/numerical method for the determination of moduli of elastic materials. Generally, all 21 elastic components of the elastic tensor can be determined by the numerical procedure based on the knowledge of a mechanical spectrum of a specimen. This involves the solution of a demanding inverse problem. Presently, Levenberg–Marquardt’s (LM) algorithm with the Ritz method for the solution of eigenfrequencies is usually applied. The LM method is based on the modified Newton–Raphson procedure, where all the eigenfrequencies and eigenvectors must be known for the computation of relevant gradients. Finite element method offers an analogous but more general optimization. The tested specimen, for instance, can be made of a composite material consisting of several layers with different material properties; the form of the specimen can be of a more complex shape, etc. In the present work, the elastic moduli are optimized by the fixed point iteration method, which r.
Optimization of single-particle basis for exactly soluble models of correlated electrons

We determine the explicit form of the single-particle wave functions ${{w}_{i}(\mathbf{r})}$ appearing in the microscopic parameters of models in the second-quantization representation. Namely, the general form of the renormalized wave equation is derived from the Lagrange-Euler principle by treating the system ground-state energy of an exact correlated state as a functional of ${{w}_{i}(\mathbf{r})}$ and their derivatives. The method is applied to three model situations with one orbital per atom. For the first example\char22{}the Hubbard chain\char22{}the optimized basis is obtained only after the electronic correlation has been included in the rigorous Lieb-Wu solution for the ground-state energy. The renormalized Wannier wave functions are obtained variationally starting from the atomic basis for the s-type wave functions. The principal characteristics such as the ground-state energy and the model parameters are calculated as a function of interatomic distance. Second, the atomic systems such as the ${\mathrm{H}}_{2}$ molecule or He atom can be treated in the same manner and the optimized orbitals are obtained to illustrate the method further. Finally, we illustrate the method by solving exactly correlated quantum dots of $Nl~8$ atoms with the subsequent optimization of the orbitals. Our method may be regarded as the next step in analyzing exactly soluble many-body models that provides properties as a function of the lattice parameter and defines at the same time the renormalized wave function for a single particle.
Pathways to social development: Rosa Luxemburg’s studies on the anthropology and sociology of imperialism

ABSTRACT While Rosa Luxemburg is widely known for her critique of reformism and political authoritarianism, less attention has been paid to her anthropological and ethnographic studies of non-Western and precapitalist societies. This chapter examines Luxemburg’s work on this in her Introduction to Political Economy and writings composed between 1907 and 1914 at the school of the German Social-Democratic Party in Berlin. In doing so, it compares and contrasts Luxemburg’s studies on the non-Western world with the late writing of Marx (1872–1883), especially concerning “the so-called primitive accumulation of capital. ”