Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct computation of aerodynamic sound

Aeroacoustic theory, which attempts to predict the acoustic far field produced by an unsteady flow, is well established for simple flows with compact vorticity fields. For turbulent shear flows which have extensive vorticity fields, a detailed agreement with experiment has been elusive, owing to a lack of knowledge of the structure of the acoustic sources. We examine the feasibility and accuracy of using the Navier-Stokes equations to directly compute (without models) a flow and its acoustic field. Given such information, aeroacoustic theory may be directly evaluated. A high-order-accurate numerical method for the Navier-Stokes equations is presented. Nonreflecting boundary conditions which allow the passage of sound waves and vortical structures through computational boundaries are developed. The efficacy of the method is firmly established by considering model problems including the scattering of sound waves by a vortex, and the sound generated by a two dimensional mixing layer. For vortex scattering, the sound waves are strongly refracted by the slowly decaying vortex flow, an effect incorrectly treated in previous theories. We develop a corrected theory which gives excellent agreement with the numerical results. For the mixing layer, the computations show that the acoustic field at the fundamental and first two subharmonic frequencies emanates from the region of the flow where the layer rolls up into vortices, and pairs twice, respectively. The acoustic waves produced by the pairings are beamed downstream, as previously observed by Laufer and Yen (1983) for the round jet. The acoustic field is also predicted by solving Lilley's equation; source terms necessary to solve the equation are determined from the Navier-Stokes computations. Predictions for the acoustic field based on our solution of Lilley's equation do not agree with the Navier-Stokes computations. Reasons for the discrepancy are examined in detail.
Nearest neighbor search on embeddings rapidly identifies distant protein relations

Since 1992, all state-of-the-art (SOTA) methods for fast and sensitive identification of evolutionary, structural, and functional relations between proteins (also referred to as “homology detection”) use sequences and sequence-profiles (PSSMs). Protein Language Models (pLMs) generalize sequences, possibly capturing the same constraints as PSSMs, e.g., through embeddings. Here, we explored how to use such embeddings for nearest neighbor searches to identify relations between protein pairs with diverged sequences (remote homology detection for levels of <20% pairwise sequence identity, PIDE). While this approach excelled for proteins with single domains, we demonstrated the current challenges applying this to multi-domain proteins and presented some ideas how to overcome existing limitations, in principle. We observed that sufficiently challenging data set separations were crucial to provide deeply relevant insights into the behavior of nearest neighbor search when applied to the protein embedding space, and made all our methods readily available for others.
Arc ubiquitination regulates endoplasmic reticulum-mediated Ca2+ release and CaMKII signaling

Synaptic plasticity relies on rapid, yet spatially precise signaling to alter synaptic strength. Arc is a brain enriched protein that is rapidly expressed during learning-related behaviors and is essential for regulating metabotropic glutamate receptor-mediated long-term depression (mGluR-LTD). We previously showed that disrupting the ubiquitination capacity of Arc enhances mGluR-LTD; however, the mechanism by which this occurs and its consequences on other mGluR-mediated signaling events is unknown. Here we show that disrupting Arc ubiquitination on key amino acid residues leads to derangements in Ca2+ release from the endoplasmic reticulum (ER) during pharmacological activation of Group I mGluRs. These alterations were observed in all neuronal subregions except secondary branchpoints. Deficits in Arc ubiquitination increased Arc self-association and enhanced its interaction with calcium/calmodulin-dependent protein kinase IIb (CaMKIIb) and constitutively active forms of CaMKII. Notably, these interactions were also excluded at secondary branchpoints. Finally, disruptions in Arc ubiquitination were found to increase Arc interaction with the integral ER protein Calnexin. These results suggest a previously unknown role for Arc ubiquitination in the fine tuning of ER-mediated Ca2+ signaling that is needed for mGluR-LTD, which in turn, may regulate CaMKII and its interactions with Arc.
The DEPDC1 protein LET-99 is required for cortical stability and antagonizes branched actin formation to promote robust cytokinesis

During cytokinesis, signals from the central spindle stimulate the accumulation of active RhoA-GTPase and thus contractile ring components at the equator, while the astral microtubules inhibit such components at the polar cortex. The DEPDC1 family protein LET-99 is required for furrow ingression in the absence of the central spindle signal, and for timely onset of furrowing even in the presence of the central spindle signal. Here we show that LET-99 works downstream or independently of RhoA-GTP and antagonizes branched F-actin and the Rac protein CED-10 to promote furrow initiation. This interaction with CED-10 is separable from LET-99’s function in spindle positioning. We also characterize a new role for LET-99 in regulating cortical stability, where LET-99 acts in parallel with the actomyosin scaffolding protein anillin, but LET-99 does not antagonize CED-10 in this case. We propose that LET-99 acts in a pathway that inhibits the Rac CED-10 to promote the proper balance of branched versus linear F-actin for cytokinesis, and that LET-99 also regulates another factor that contributes to cortical stability.
Visual object topographic motifs emerge from self-organization of a unified representational space

The object-responsive cortex of the visual system has a highly systematic topography, with a macro-scale organization related to animacy and the real-world size of objects, and embedded meso-scale regions with strong selectivity for a handful of object categories. Here, we use self-organizing principles to learn a topographic representation of the data manifold of a deep neural network representational space. We find that a smooth mapping of this representational space showed many brain-like motifs, with (i) large-scale organization of animate vs. inanimate and big vs. small response preferences, supported by (ii) feature tuning related to textural and coarse form information, with (iii) naturally emerging face- and scene-selective regions embedded in this larger-scale organization. While some theories of the object-selective cortex posit that these differently tuned regions of the brain reflect a collection of distinctly specified functional modules, the present work provides computational support for an alternate hypothesis that the tuning and topography of the object-selective cortex reflects a smooth mapping of a unified representational space.
Early life adversity and adult social relationships have independent effects on survival in a wild animal model of aging

Does social isolation in adulthood predict survival because socially isolated individuals are already unhealthy due to adversity earlier in life (health selection)? Or do adult social environments directly cause poor health and increased mortality risk (“social causation”)? These alternative hypotheses are difficult to disentangle in humans because prospective data on survival and the environment for both early life and adulthood are rarely available. Using data from the baboon population of Amboseli, Kenya, a model for human behavior and aging, we show that early adversity and adult social isolation contribute independently to reduced adult survival, in support of both health selection and social causation. Further, strong social bonds and high social status can buffer some negative effects of early adversity on survival. These results support a growing change in perspective, away from “either-or” hypotheses and towards a multi-causal perspective that points to multiple opportunities to mitigate the effects of social adversity. Teaser Early life environments and adult social bonds have strong, but largely independent effects on survival in wild baboons.
Exposure to global change and microplastics elicits an immune response in an endangered coral

Global change is increasing seawater temperatures and decreasing oceanic pH, driving declines of coral reefs globally. Coral ecosystems are also impacted by local stressors, including microplastics, which are ubiquitous on reefs. While the independent effects of these global and local stressors are well-documented, their interactions remain less explored. Here, we examine the independent and combined effects of global change (ocean warming and acidification) and microplastics exposures on gene expression (GE) and microbial community composition in the endangered coral Acropora cervicornis. Nine genotypes were fragmented and maintained in one of four experimental treatments: 1) ambient conditions (ambient seawater, no microplastics; AMB); 2) microplastics treatment (ambient seawater, microplastics; MP); 3) global change conditions (warm and acidic conditions, no microplastics; OAW); and 4) multistressor treatment (warm and acidic conditions with microplastics; OAW+MP) for 22 days, after which corals were sampled for genome-wide GE profiling and ITS and 16S metabarcoding. Overall A. cervicornis GE responses to all treatments were subtle; however, corals in the multistressor treatment exhibited the strongest GE responses, and genes associated with innate immunity were overrepresented in this treatment, according to gene ontology enrichment analyses. 16S analyses revealed stable microbiomes dominated by the bacterial associate Aquarickettsia, suggesting that these A. cervicornis fragments exhibited remarkably low variability in bacterial community composition. Future work should focus on functional differences across microbiomes, especially Aquarickettsia and viruses, in these responses. Overall, results suggest that local stressors present a unique challenge to endangered coral species under global change.
MAGE enables population level RNAseq driven genotyping and (differential) allelic divergence detection in healthy kidney and carcinoma

Decreasing sequencing costs have instigated large-scale RNAseq experiments, yet genetic polymorphisms in such data remain poorly exploited. Currently, allele-specific expression (ASE) studies focus almost exclusively on genetic variants explaining expression differences (cis-eQTLs), largely ignoring other ASE effects. The latter are typically associated with higher variance in expression of both copies of a gene, here called Allelic Divergence (AD). We therefore developed an RNAseq-driven population-level beta-binomial mixture model for (differential) AD detection. The model simultaneously enables RNAseq-driven genotyping, which outperforms alternative RNA genotyping methods when applied on healthy kidney data from The Cancer Genome Atlas. Moreover, we identify well-known non-cis-eQTL ASE, e.g. random monoallelic expression of HLA and immunoglobulin genes in healthy kidney, as well as allele-specific aberrations in clear cell kidney carcinoma, including long-range epigenetic silencing of protocadherins, copy-number alterations, and loss of imprinting. These methods are available as the Modeller of Allelic Gene Expression (MAGE) tool suite: https://biobix.github. io/MAGE/.
Novel Laser Capture Microdissection-Proteomic Analysis Identifies Spatially Distinct Extracellular Matrix Signatures in the Core and Infiltrating Edge of Human Glioblastoma

Background Glioblastoma is the most common and aggressive primary brain tumour in adults. Hallmarks of glioblastoma include its intra-tumoural heterogeneity and extensive invasion of the surrounding brain. Glioblastoma is known to remodel the extracellular matrix (ECM) of the brain, resulting in altered mechanical properties and the establishment of a tumour-promoting microenvironment. How changes in the expression and spatial distribution of ECM constituents within glioblastoma contribute to invasion and disease progression is still unclear. Methods Here we report on a protocol for laser-capture microdissection coupled with mass spectrometry (LCM-proteomics) that allowed a spatially resolved and unbiased analysis of the regional ECM proteome (matrisome) in formalin-fixed and paraffin-embedded (FFPE) samples of human glioblastoma. We investigated five molecularly characterised hemispheric adult glioblastomas where the brain/tumour interface and tumour epicentre were represented in the surgical specimens and snap-frozen tissue was available. LCM-proteomic analysis was validated with immunohistochemistry. Results LCM-proteomics identified 53 matrisome proteins in FFPE tissue, demonstrating comparable performance with conventional analysis of snap-frozen tissue. The analysis revealed distinct matrisome components in the brain/tumour interface versus the tumour epicentre. Guided by data from LCM-proteomic analysis, immunostaining for tenascin-R confirmed greater staining in the brain/tumour interface, whilst expression of fibronectin was higher in the tumour epicentre. Conclusion The protocol described in this work allowed for accurate, spatially resolved analysis of ECM in FFPE tissues, with performance comparable to analysis of snap-frozen tissue. While the focus for this work was on the regional ECM composition of glioblastoma, we found that the LCM-proteomics protocol is also applicable to the study of the wider proteome, and represents a valuable tool for investigating tumour/tissue heterogeneity. This protocol opens the possibility to apply LCM-proteomics to retrospective studies with the advantage of accessing clinical history and follow-up information, providing a valuable resource for translational research in glioblastoma.
Fusion-negative Rhabdomyosarcoma 3D-organoids as an innovative model to predict resistance to cell death inducers

Rhabdomyosarcoma (RMS) is the main form of soft-tissue sarcoma in children and adolescents. For 20 years, and despite international clinical trials, its cure rate has not really improved, and remains stuck at 20% in case of relapse. The definition of new effective therapeutic combinations is hampered by the lack of reliable models, which complicate the transposition of promising results obtained in pre-clinical studies into efficient solutions for young patients. Inter-patient heterogeneity, particularly in the so-called fusion-negative group (FNRMS), adds an additional level of difficulty in optimizing the clinical management of children and adolescents with RMS. Here, we describe an original 3D-organoid model derived from relapsed FNRMS and show that it finely mimics the characteristics of the original tumor, including inter- and intra-tumoral heterogeneity. Moreover, we have established the proof-of-concept of their preclinical potential by re-evaluating the therapeutic opportunities of targeting apoptosis in FNRMS from a streamlined approach based on the exploitation of bulk and single-cell omics data.
The history of multisensory discrepancies affects the ventriloquism effect and the immediate aftereffect differentially

Multisensory integration and recalibration are two processes by which perception deals with discrepant multisensory signals. In the lab, integration can be probed via the presentation of simultaneous spatially discrepant audio ‐ visual stimuli, i.e. in a spatial ventriloquism paradigm. Recalibration here manifests as an aftereffect bias in unisensory judgements following immediate or long ‐ term exposure to discrepant audio ‐ visual stimuli. Despite many studies exploring the ventriloquism effect (VE) and the immediate aftereffect (VAE), it remains unclear whether the VAE is a direct consequence of the integration of preceding discrepant multisensory signals. We here provide evidence that these two biases are not strictly related. First, we analysed data from ten experiments probing the dependence of each bias on audio ‐ visual discrepancies experienced in multiple preceding trials. This revealed a seven ‐ fold stronger dependence of the VAE on preceding discrepancies compared to the VE. Second, we analysed data from an experiment deviating from the typical trial context in which these biases are probed and found that the VAE can vanish despite the VE being present. We argue that integration may help maintaining a stable percept by reducing immediate sensory discrepancies, whereas recalibration may help maintaining an accurate percept by accounting for consistent discrepancies. Hence, the immediate VAE is not a direct and necessary consequence of the integration of discrepant signals and these two well ‐ studied multisensory response biases can be experimentally dissociated.
African swine fever virus – variants on the rise

African swine fever virus (ASFV), a large and complex DNA-virus circulating between soft ticks and indigenous suids in sub-Saharan Africa, has made its way into swine populations from Europe to Asia. This virus, causing a severe haemorrhagic disease (African swine fever) with very high lethality rates in wild boar and domestic pigs, has demonstrated a remarkably high genetic stability for over 10 years. Consequently, analyses into virus evolution and molecular epidemiology often struggled to provide the genetic basis to trace outbreaks while few resources have been dedicated to genomic surveillance on whole-genome level. During its recent incursion into Germany in 2020, ASFV has unexpectedly diverged into five clearly distinguishable linages with at least ten different variants characterized by high-impact mutations never identified before. Noticeably, all new variants share a frameshift mutation in the 3’ end of the DNA polymerase PolX gene O174L, suggesting a causative role as possible mutator gene. Although epidemiological modelling supported the influence of increased mutation rates, it remains unknown how fast virus evolution might progress under these circumstances. Moreover, a tailored Sanger sequencing approach allowed us, for the first time, to trace variants with genomic epidemiology to regional clusters. In conclusion, our findings suggest that this new factor has the potential to dramatically influence the course of the ASFV pandemic with unknown outcome. Therefore, our work highlights the importance of genomic surveillance of ASFV on whole-genome level, the need for high-quality sequences and calls for a closer monitoring of future phenotypic changes of ASFV.
Utility of stromal lymphocytes in diagnosis and predicting upgrade of B3 breast lesions from core biopsies

For more than two decades attempts have been made to identify a subset of women diagnosed with lesions with uncertain malignant potential (B3 lesions) who could safely be observed rather than being treated with surgical excision and/or chemoprevention. Various histopathological, clinical and imaging parameters for risk recommendation have been evaluated, with little impact on clinical practice. The primary reason for surgery is to rule out an upgrade lesion to either ductal carcinoma in situ (DCIS) or invasive breast cancer (IBC). While on average 30% of these patients are upgraded after diagnostic biopsy, a large number are over treated,making this an important harm of screening. Here we evaluated stromal lymphocytes from B3 biopsies (n=264) as a predictive biomarker for upgrade. A higher number of stromal lymphocytes were observed in upgraded B3 lesions than non-upgraded (p< 0.01, zero inflated binomial model) for both ductal and papillary lesions (n=174). This observation was validated in an independent cohort (p<0.001, p<0.05, zero binomial model, ductal and papillary lesions, respectively) (n=90). Our data suggested that the presence of ≥5% of lymphocytes in the surrounding specialised stroma of B3 lesions are predictive of B3 lesions being upgraded with a specificity of 93% and 87% in our discovery and validation cohorts, respectively. The area under the curve (AUC) for the discovery cohort using lymphocyte count and age as variables was 0.77 and was validated with an AUC of 0.81 in the validation cohort. In conclusion, we can identify a subset of the patients at risk of upgrade with high specificity. Assessing the tumour microenvironment including stromal lymphocytes may contribute to reducing unnecessary surgeries in the clinic.
Molecular Simulations and NMR Reveal How Lipid Fluctuations Affect Membrane Mechanics

Lipid bilayers form the main matrix of functional cell membranes, and their dynamics underlie a host of physical and biological processes. Here we show that elastic membrane properties and collective molecular dynamics are related by the mean-square amplitudes (order parameters) and relaxation rates (correlation times) of lipid acyl chain motions. We performed all-atom molecular dynamics simulations of liquid-crystalline bilayers to further interpret available NMR data. Our analysis entailed development of a theoretical framework that allows direct comparison of carbon-hydrogen (CH) bond relaxations as measured by simulations and NMR experiments. The new formalism enables validation of lipid force fields against NMR data by including a fixed bilayer normal (director axis) and restricted anisotropic motion of the CH bonds described by their segmental order parameters. The simulated spectral density of thermally excited CH bond fluctuations exhibited well-defined spin-lattice (Zeeman) relaxations analogous to those measured by solid-state NMR spectroscopy. Their frequency signature could be fit to a simple power-law function, indicative of collective dynamics of a nematic-like nature. The calculated spin-lattice relaxation rates scaled as the squared order parameters of the lipid acyl chains yielding an apparent bending modulus κC of the bilayer. Our results show a strong correlation with κC values obtained from solid-state NMR studies of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) bilayers with varying amounts of cholesterol as further validated by neutron spin-echo measurements of membrane elasticity. The simulations uncover a critical role of interleaflet coupling in membrane mechanics and thus provide insights into the molecular sites of emerging elastic properties within lipid bilayers. STATEMENT OF SIGNIFICANCE The lipid make-up of a bilayer determines its measurable properties but how the motions of individual molecules combine to produce these properties remains unclear. By exploiting the synergy between NMR spectroscopy and molecular dynamics (MD) simulations, we show that the lipid dynamics in a bilayer are collective yet segmental in nature and contribute directly to bilayer elasticity. Comparison between MD simulations and NMR entails an improved theoretical framework that allows the two techniques to be directly related. This study thus provides novel insights into the inner workings of lipid membranes while delivering a new tool for validating computational approaches against experimental data.