Miracle-dz/UniFAR-FTUs huggingface dataset:
Regulation of transcription patterns, poly-ADP-ribose, and RNA-DNA hybrids by the ATM protein kinase

The ATM protein kinase is a master regulator of the DNA damage response and also an important sensor of oxidative stress. Analysis of gene expression in Ataxia-telangiectasia patient brain tissue shows that large-scale transcriptional changes occur in patient cerebellum that correlate with expression level and GC content of transcribed genes. In human neuron-like cells in culture we map locations of poly-ADP-ribose and RNA-DNA hybrid accumulation genome-wide with ATM inhibition and find that these marks also coincide with high transcription levels, active transcription histone marks, and high GC content. Antioxidant treatment reverses the accumulation of R-loops in transcribed regions, consistent with the central role of ROS in promoting these lesions. Based on these results we postulate that transcription-associated lesions accumulate in ATM-deficient cells and that the single-strand breaks and PARylation at these sites ultimately generate changes in transcription that compromise cerebellum function and lead to neurodegeneration over time in A-T patients.
Maintenance and evolution of individual differences in a prey defence trait examined with a dynamic predator-prey model

Predator-prey systems often feature periodic population cycles. In an empirical system with a heritable prey defence trait, ecological oscillations were previously shown to cause evolution of prey defence on the timescale of the population cycles. In this paper, we develop an eco-evolutionary mathematical model comprising partial differential equations to investigate the evolutionary dynamics of prey defence during population cycles. We reveal that ecological population cycles induce evolutionary oscillations of the mean prey defence trait. In contrast to existing continuum modelling frameworks, our model allows for the evolution of individual variability. We show that eco-evolutionary oscillations select for increased individual variability close to the transition from stable to oscillatory states. We also reveal that evolution of prey defence requires both high efficiency and low cost of prey defence and highlight that more information on trade-offs between cost and efficiency is required.
Stimulus selection influences prediction of individual phenotypes in naturalistic conditions

Understanding individual differences and brain-behaviour relationships is an essential goal of human neuroscience. Recent studies have shown the great potential of naturalistic stimuli, e.g., movie clips, in advancing this pursuit. While the use of naturalistic stimuli attracts increasing interest, the influence of stimulus selection remains largely unclear. In this study, we show that brain activity is generally sensitive to the choice of movie stimuli at both group and individual subject levels. Using sex classification as an example, we demonstrate that brain activity elicited by different stimuli can lead to distinct prediction performance and unique predictive features. The stimuli that yield better classification performance often elicit stronger synchrony of brain activity across all subjects and are mostly derived from Hollywood films with rich social content and cohesive narratives. Our results highlight the importance of stimulus selection and provide practical guidance for choosing appropriate stimuli, opening up new avenues for future studies on individual differences and brain-behaviour relationships.
The dysregulated IL-23/TH17 axis in endometriosis pathophysiology

Endometriosis is a chronic inflammatory disease where endometrial-like tissue grows ectopically, resulting in pelvic pain and infertility. Interleukin (IL)-23 is established as a key contributor in the development and differentiation of a subset of T cells known as T-helper 17 (TH17) cells, driving TH17 cells towards a pathogenic profile. In a variety of inflammatory and autoimmune disorders, such as psoriasis and rheumatoid arthritis, TH17 cells secrete proinflammatory cytokines including IL-17, contributing to the disease pathophysiology. Our studies and others have implicated IL-17 and TH17 cell dysregulation in endometriosis, which is associated with disease severity. Here we address whether IL-23 driven TH17 cells contribute to the cardinal features of lesion proliferation, vascularization, and inflammation in endometriosis using patient samples, representative cell lines, and our established mouse model of endometriosis. Our results indicate significantly dysregulated expression of key genes in the IL-23/TH17 axis in patient ectopic and eutopic endometrial samples and increased IL-23 protein in patient plasma compared to healthy controls. In-vitro studies using primary human TH cells determined that IL-23 cocktail treatment significantly increased the frequency of pathogenic TH17 cells. Similarly, treatment with recombinant human (rh)IL-23 on cell lines (12Z, EECC, HUVEC, and hESC) representative of the endometriotic lesion microenvironment led to a significant increase in cytokines and growth factors known to play a role in lesion establishment and maintenance. In a syngeneic mouse model of endometriosis, treatment with recombinant mouse (rm)IL-23 led to significant alterations in numbers of myeloid and T cell subsets in peritoneal fluid and significantly increased numbers of giant cells within the lesion. Endometriotic lesions from rmIL-23 mice did not reveal significant alterations in proliferation and vascularization, although trends of increased proliferation and vascularization were observed. Collectively, these findings provide insights into the impact of the IL-23/TH17 axis on local immune dysfunction and broadly on the pathophysiology of endometriosis.
Specific inhibition of α-synuclein oligomer generation and toxicity by the chaperone domain Bri2 BRICHOS

Understanding the molecular mechanisms of neurodegenerative diseases and finding efficient treatments have been major priorities for research and society, yet new therapeutic approaches remain essential to face the socio-economic burden caused by these devastating diseases. Protein misfolding and aggregation are involved in several neurodegenerative disorders, such as α-synuclein (αSyn) implicated in Parkinson’s disease. Elucidating the microscopic nucleation mechanisms has opened new opportunities to develop therapeutics against toxic mechanisms and species. Here, we show that naturally occurring molecular chaperones, represented by the anti-amyloid Bri2 BRICHOS domain, can be used to target αSyn-associated nucleation processes and structural species related to neurotoxicity. Our findings revealed that BRICHOS predominately suppresses the formation of new nucleation units on the fibrils surface (secondary nucleation), in addition to fibril-end elongation. This mechanism implies a drastic decrease of the oligomer generation rate. Besides targeting secondary nucleation sites on the fibril surface, BRICHOS directly binds to oligomeric αSyn species. Further, using ex vivo experiments, BRICHOS effectively diminishes αSyn fibril-related toxicity to hippocampal electrophysiology. Our studies show that molecular chaperones can be utilized as tools to target molecular processes and structural species related to αSyn neurotoxicity and have the potential as protein-based treatments against neurodegenerative disorders.
Single-Molecule FRET at 10 MHz Count Rates

A bottleneck in many studies utilizing single-molecule Förster Resonance Energy Transfer (smFRET) is the attainable photon count rate as it determines the temporal resolution of the experiment. As many biologically relevant processes occur on timescales that are hardly accessible with currently achievable photon count rates, there has been considerable effort to find strategies to increase the stability and brightness of fluorescent dyes. Here, we use DNA nanoantennas to drastically increase the achievable photon count rates and to observe fast biomolecular dynamics in the small volume between two plasmonic nanoparticles. As a proof of concept, we observe the coupled folding and binding of two intrinsically disordered proteins which form transient encounter complexes with lifetimes on the order of 100 μs. To test the limits of our approach, we also investigated the hybridization of a short single-stranded DNA to its complementary counterpart, revealing a transition path time of 17 μs at photon count rates of around 10 MHz, which is an order-of-magnitude improvement when compared to the state of the art. Concomitantly, the photostability was increased, enabling many seconds long megahertz fluorescence time traces. Due to the modular nature of the DNA origami method, this platform can be adapted to a broad range of biomolecules, providing a promising approach to study previously unobservable ultrafast biophysical processes.
Structural studies of a serum amyloid A octamer that is primed to scaffold lipid nanodiscs

Serum amyloid A (SAA) is a highly conserved acute-phase protein that acts on multiple pro-inflammatory pathways during the inflammatory response and is used as a biomarker of inflammation. It has also been linked to beneficial roles in tissue repair through improved clearance of lipids and cholesterol. In patients with chronic inflammatory diseases, elevated SAA may contribute to increased severity of the underlying condition. The majority of circulating SAA is bound to high-density lipoprotein (HDL), stabilizing SAA and altering its functional properties, likely through altered accessibility of protein-protein interaction sites on SAA. While high-resolution structures for lipid-free forms of SAA have been reported, their relationship with the lipid or HDL-bound forms of the protein, has not been established. We used multiple biophysical techniques, including SAXS, TEM, SEC-MALS, native gel electrophoresis, glutaraldehyde crosslinking, and trypsin digestion to characterize the lipid-free and lipid-bound forms of SAA. SAXS and TEM data show the presence of soluble octamers of SAA with structural similarity to the ring-like structures reported for lipid-free ApoA-I. These SAA octamers represent a previously uncharacterized structure for lipid-free SAA and are capable of scaffolding lipid nanodiscs with similar morphology to those formed by ApoA-I. SAA-lipid nanodiscs contain four SAA molecules and have similar exterior dimensions as the lipid-free SAA octamer, suggesting that relatively few conformational rearrangements are required for lipid binding. This study suggests a new model for SAA-lipid interactions and provides new insight into the ability of SAA to stabilize protein-lipid nanodiscs or even replace ApoA-I on HDL particles during inflammation.
The Exon Junction Complex component EIF4A3 plays a splicing-linked oncogenic role in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide and further research on its biology is needed to fully understand the disease. Dysregulation of alternative RNA splicing is a common hallmark in cancer, including PDAC, which provides an emerging source of knowledge and of novel biomarkers and therapeutic tools. Here, we examined the role of EIF4A3, a core component of the Exon Junction Complex intimately linked to RNA splicing, in pancreatic cancer biology. EIF4A3 is overexpressed in PDAC tissue and associated to clinical parameters of malignancy and poorer patient survival. Mechanistically, exploration of PDAC RNA-seq data unveiled the link of EIF4A3 to diverse malignancy processes, in line with its association to key molecular pathways. Accordingly, EIF4A3 targeting in vitro decreased essential functional tumor features such as proliferation, migration, colony formation and sphere formation, while its in vivo targeting reduced tumor growth. EIF4A3 silencing in PDAC cell lines severely altered its transcriptional and spliceosomic landscapes, as shown by RNA-seq analyses, suggesting a role for EIF4A3 in maintaining RNA homeostasis. Our results indicate that EIF4A3 dysregulation in PDAC has a pleiotropic regulatory role on RNA biology, influencing key cellular functions. This paves the way to explore its potential as a novel biomarker and actionable target candidate for this lethal cancer.
Two distinct modes of hemodynamic responses in the human brain

Functional magnetic resonance imaging (fMRI) detects changes in brain activity by measuring fluctuations in blood oxygenation. While fMRI assumes a fixed relationship between changes in cerebral blood flow (CBF) and metabolic activity, its uniform application across the human cortex lacks complete validation. We used quantitative fMRI together with blood oxygenation level-dependent (BOLD) fMRI to assess oxygen metabolism against both positive and negative BOLD signal changes. We found a surprising mismatch between changes in oxygen consumption and the direction of BOLD signal changes (ΔBOLD) in 14-33% of voxels with significant positive, and in 50-66% of voxels with significant negative ΔBOLD. This implies that a substantial number of voxels with negative ΔBOLD actually demonstrate increased metabolic activity, and vice versa. Contrary to the canonical hemodynamic response model, discordant voxels cover their oxygen demand predominantly via changes in the oxygen extraction fraction (ΔOEF) and not via ΔCBF. This coincides with a higher vascular density and a lower OEF during baseline that we identified in discordant voxels. In summary, we identified a second type of hemodynamic response mechanism for regulating oxygen supply in the human brain. Our results suggest that the classical interpretation of positive and negative BOLD signal changes in terms of increased or decreased neural activity may be too simplistic and we recommend incorporating quantitative MRI or additional CBF measurements for a more accurate assessment of neuronal activity.
Signalling-state dependent drug-tolerance in head and neck squamous cell carcinoma

Intratumor heterogeneity negatively impacts therapeutic response and patient prognosis. Besides the established role of genetic heterogeneity, non-genetic mechanisms of persistence to drug treatment are emerging. Here, we characterise cells selected for their persistence to control, epidermal growth factor inhibition (EGFRi), radiation and combined treatment from low passage head and neck squamous cell carcinoma (HNSCC) cultures. Using a panel of 70 (phospho-)specific DNA-conjugated antibodies we measured activities of 8 signalling pathways, self-renewal, differentiation, DNA damage and cell-cycle, in conjunction with the transcriptional output in single cells, using our RNA and Immuno-Detection (RAID) technology. Six recurrent transcriptional programs reflecting processes including proliferation, differentiation and metabolic activity, as well as protein-based signalling-states, were associated with drug persistence, while copy number variation inference indicated involvement of non-genetic tolerance mechanisms. Projecting RNA velocity onto the antibody-derived signalling-states suggested a key role for integrin-mediated focal-adhesion signalling in drug-persistence in our cell system. Using machine-learning we derived a core transcriptional signature connected to adhesion-based drug-persistence, which was predictive of poor prognosis in a TGCA HNSCC cohort (hazard-ratio 1.87, p<10-5). Furthermore, functional analyses confirmed that cells expressing high levels of integrin alpha-6 (ITGA6) were tolerant to EGFRi treatment, and that forcing cells out of this cell-state through transient targeted inhibition of Focal Adhesion Kinase activity re-instated EGFRi sensitivity in drug persistent cells. Taken together, our single-cell multi-omics analysis identified an actionable adhesion-signalling mediated cell-state driving drug tolerance in HNSCC.
Divergent Epigenetic and Transcriptomic Reprogramming of Monocyte Subpopulations in Systemic Lupus Erythematosus

Systemic Lupus Erythematosus (SLE) is an autoimmune disease characterized by systemic inflammation involving various immune cell types. Monocytes, pivotal in promoting and regulating inflammation in SLE, differentiate from classical monocytes into intermediate monocytes and non-classical monocytes, assuming diverse roles. In this study, we investigated the epigenetic and transcriptomic profiles of these three monocyte subsets in an SLE cohort. In addition to common DNA methylation and transcriptomic alterations, we identified monocyte subset-specific alterations, especially in DNA methylation, which reflect an impact of SLE on the monocyte differentiation process. SLE classical monocytes exhibited a stronger proinflammatory profile, with an interferon signature and were primed for macrophage differentiation. SLE non-classical monocytes displayed a phenotype related to T cell differentiation regulation, and a Th17-promoting phenotype. Changes in monocyte proportions, DNA methylation and expression occurred in relation to disease activity and involved the STAT1 pathway. Integrating bulk datasets with single-cell RNA-seq data of SLE patients further supported the interferon signature in classical monocytes, associating intermediate and non-classical populations with exacerbated complement activation pathways. Our results indicate a subversion of the epigenome and transcriptome in monocyte differentiation toward non-classical subsets in SLE, impacting function, in relation to disease activity and progression.
Cell-state transitions and frequency-dependent interactions among subpopulations together explain the dynamics of spontaneous epithelial-mesenchymal heterogeneity in breast cancer

Individual cells in a tumour can be distributed among Epithelial (E) and Mesenchymal (M) cell-states, as characterised by the levels of canonical E and M markers. Even after E and M (E-M) subpopulations are isolated and then cultured independently, E-M heterogeneity can re-equilibrate in each population over time, sometimes regaining the initial distribution of the parental cell population. However, it remains unclear which population-level processes give rise to the dynamical changes in E-M heterogeneity observed experimentally, including 1) differential growth, 2) cell-state switching, and 3) frequency-dependent growth or state-transition rates. Here, we analyse the necessity of these three processes in explaining the dynamics of E-M population distributions as observed in PMC42-LA and HCC38 breast cancer cells. We find that growth differences among E and M subpopulations, with and without any frequency-dependent interactions (cooperation or suppression) among E-M sub-populations, are insufficient to explain the observed population dynamics. This insufficiency is ameliorated by including cell-state transitions, albeit at slow rates, in explaining both PMC42-LA and HCC38 cells data. Further, our models predict that treatment of HCC38 cells with TGFβ signalling and JAK2/3 inhibitors could significantly enhance the transition rates from M state to E state, but does not prevent transitions from E to M. Finally, we devise a selection criterion to identify the next most informative time points for which future experimental data can optimally improve the identifiability of our estimated best fit model parameters. Overall, our study identifies the necessary population-level processes shaping the dynamics of E-M heterogeneity in breast cancer cells.
ToViLaG: Your Visual-Language Generative Model is Also An Evildoer

Warning: this paper includes model outputs showing offensive content. Recent large-scale Visual-Language Generative Models (VLGMs) have achieved unprecedented improvement in multimodal image/text generation. However, these models might also generate toxic content, e.g., offensive text and pornography images, raising significant ethical risks. Despite exhaustive studies on toxic degeneration of language models, this problem remains largely unexplored within the context of visual-language generation. This work delves into the propensity for toxicity generation and susceptibility to toxic data across various VLGMs. For this purpose, we built ToViLaG, a dataset comprising 32K co-toxic/mono-toxic text-image pairs and 1K innocuous but evocative text that tends to stimulate toxicity. Furthermore, we propose WInToRe, a novel toxicity metric tailored to visual-language generation, which theoretically reflects different aspects of toxicity considering both input and output. On such a basis, we benchmarked the toxicity of a diverse spectrum of VLGMs and discovered that some models do more evil than expected while some are more vulnerable to infection, underscoring the necessity of VLGMs detoxification. Therefore, we develop an innovative bottleneck-based detoxification method. Our method could reduce toxicity while maintaining comparable generation quality, providing a promising initial solution to this line of research.
Causal Reasoning through Two Cognition Layers for Improving Generalization in Visual Question Answering

Generalization in Visual Question Answering (VQA) requires models to answer questions about images with contexts beyond the training distribution. Existing attempts primarily refine unimodal aspects, overlooking enhancements in multimodal aspects. Besides, diverse interpretations of the input lead to various modes of answer generation, highlighting the role of causal reasoning between interpreting and answering steps in VQA. Through this lens, we propose Cognitive pathways VQA (CopVQA) improving the multimodal predictions by emphasizing causal reasoning factors. CopVQA first operates a pool of pathways that capture diverse causal reasoning flows through interpreting and answering stages. Mirroring human cognition, we decompose the responsibility of each stage into distinct experts and a cognition-enabled component (CC). The two CCs strategically execute one expert for each stage at a time. Finally, we prioritize answer predictions governed by pathways involving both CCs while disregarding answers produced by either CC, thereby emphasizing causal reasoning and supporting generalization. Our experiments on real-life and medical data consistently verify that CopVQA improves VQA performance and generalization across base-lines and domains. Notably, CopVQA achieves a new state-of-the-art (SOTA) on the PathVQA dataset and comparable accuracy to the current SOTA on VQA-CPv2, VQAv2, and VQA-RAD, with one-fourth of the model size.
Characteristics and Variations of the East Asian Monsoon System and Its Impacts on Climate Disasters in China

在结构的特征的研究和东方亚洲季风(电动会计记帐机) 的时间空间的变化的最近的进展系统和在中国的严重气候灾难上的这个系统的影响被考察。 以前的研究在电动会计记帐机区域改进了我们水平、垂直的结构的基本特征和 EAM 系统和水汽运输的年度周期的理解。 许多研究证明了 EAM 系统是亚洲澳大利亚人的季风系统的一个相对独立的分系统，并且那在那里存在有南方的 tripole 模式分布在的明显的伪二年的摆动内部电动会计记帐机系统的年变化。 基本物理过程的进一步的分析，内部、外部，那影响 EAM 系统的可变性当 atmosphere-ocean-land 联合了系统，显示 EAM 系统可以被看，在这篇论文指了电动会计记帐机气候系统。 进一步，纸讨论在这个系统的各种各样的部件之中的相互作用和关系怎么能在东亚上沿着西的喷气通过东亚太平洋(EAP ) 电视连接模式和南方的 upper-tropospheric 风异例的电视连接模式被描述。 如此的推理建议分别地，在 Yangtze 和 Huaihe 河山谷的严重洪水和在诺思中国的延长干旱的出现被连接到背景内部 EAM 气候系统的年度、内部的十的可变性。 而且，与电动会计记帐机系统有关的突出的科学问题和它在中国的气候灾难上的影响也被讨论。