Do self-supervised speech and language models extract similar representations as human brain?

Speech and language models trained through self-supervised learning (SSL) demonstrate strong alignment with brain activity during speech and language perception. However, given their distinct training modalities, it remains unclear whether they correlate with the same neural aspects. We directly address this question by evaluating the brain prediction performance of two representative SSL models, Wav2Vec2.0 and GPT-2, designed for speech and language tasks. Our findings reveal that both models accurately predict speech responses in the auditory cortex, with a significant correlation between their brain predictions. Notably, shared speech contextual information between Wav2Vec2.0 and GPT-2 accounts for the majority of explained variance in brain activity, surpassing static semantic and lower-level acoustic-phonetic information. These results underscore the convergence of speech contextual representations in SSL models and their alignment with the neural network underlying speech perception, offering valuable insights into both SSL models and the neural basis of speech and language processing.Comment: To appear in 2024 IEEE International Conference on Acoustics, Speech and Signal Processin

AMP peptide targets tight junctions to protect and heal barrier structure and function in models of IBD.

Background: A peptide derived from Antrum Mucosal Protein (AMP)-18 (gastrokine-1) reduces the extent of mucosal erosions and clinical severity in mice with dextran sulfate sodium (DSS)-induced colonic injury. The present study set out to determine if AMP peptide was also therapeutic for immune- and cytokine-mediated mouse models of intestinal injury and inflammatory bowel diseases (IBD) by enhancing and stabilizing tight junctions (TJs). Methods: Therapeutic effects of AMP peptide were examined in interleukin-10 deficient and a T cell adoptive transfer models of colitis in immunodeficient recombinase activating gene-1 knock-out (RAG-1−/−) mice. Mechanisms by which AMP peptide enhances barrier function and structure were studied ex vivo using intestine and colon from mice given lipopolysaccharide (LPS), and in AMP-18 deficient mice given DSS. Results: In interleukin-10 deficient mice given piroxicam, AMP peptide enhanced recovery after weight loss, protected against colon shortening and segmental dilation, and reduced the colitis activity score. In the T cell transfer model, treatment with the peptide protected against colon shortening. In mice given LPS in vivo to induce gut injury, AMP peptide prevented the onset of, and reversed established intestinal hyperpermeability by targeting TJ proteins and perijunctional actin

A Novel Peptide for Simultaneously Enhanced Treatment of Head and Neck Cancer and Mitigation of Oral Mucositis

We have characterized a novel 21 amino acid-peptide derived from Antrum Mucosal Protein (AMP)-18 that mediates growth promotion of cultured normal epithelial cells and mitigates radiation-induced oral mucositis in animal models, while suppressing in vitro function of cancer cells. The objective of this study was to evaluate these dual potential therapeutic effects of AMP peptide in a clinically relevant animal model of head and neck cancer (HNC) by simultaneously assessing its effect on tumor growth and radiation-induced oral mucositis in an orthotopic model of HNC. Bioluminescent SCC-25 HNC cells were injected into the anterior tongue and tumors that formed were then subjected to focal radiation treatment. Tumor size was assessed using an in vivo imaging system, and the extent of oral mucositis was compared between animals treated with AMP peptide or vehicle (controls). Synergism between AMP peptide and radiation therapy was suggested by the finding that tumors in the AMP peptide/radiation therapy cohort demonstrated inhibited growth vs. radiation therapy-only treated tumors, while AMP peptide-treatment delayed the onset and reduced the severity of radiation therapy-induced oral mucositis. A differential effect on apoptosis appears to be one mechanism by which AMP-18 can stimulate growth and repair of injured mucosal epithelial cells while inhibiting proliferation of HNC cells. RNA microarray analysis identified pathways that are differentially targeted by AMP-18 in HNC vs. nontransformed cells. These observations confirm the notion that normal cells and tumor cells may respond differently to common biological stimuli, and that leveraging this finding in the case of AMP-18 may provide a clinically relevant opportunity

Efficient gene editing in adult mouse livers via adenoviral delivery of CRISPR/Cas9

AbstractWe developed an adenovirus-based CRISPR/Cas9 system for gene editing in vivo. In the liver, we demonstrated that the system could reach the level of tissue-specific gene knockout, resulting in phenotypic changes. Given the wide spectrum of cell types susceptible to adenoviral infection, and the fact that adenoviral genome rarely integrates into its host cell genome, we believe the adenovirus-based CRISPR/Cas9 system will find applications in a variety of experimental settings

SLX4 Assembles a Telomere Maintenance Toolkit by Bridging Multiple Endonucleases with Telomeres

SummarySLX4 interacts with several endonucleases to resolve structural barriers in DNA metabolism. SLX4 also interacts with telomeric protein TRF2 in human cells. The molecular mechanism of these interactions at telomeres remains unknown. Here, we report the crystal structure of the TRF2-binding motif of SLX4 (SLX4TBM) in complex with the TRFH domain of TRF2 (TRF2TRFH) and map the interactions of SLX4 with endonucleases SLX1, XPF, and MUS81. TRF2 recognizes a unique HxLxP motif on SLX4 via the peptide-binding site in its TRFH domain. Telomeric localization of SLX4 and associated nucleases depend on the SLX4-endonuclease and SLX4-TRF2 interactions and the protein levels of SLX4 and TRF2. SLX4 assembles an endonuclease toolkit that negatively regulates telomere length via SLX1-catalyzed nucleolytic resolution of telomere DNA structures. We propose that the SLX4-TRF2 complex serves as a double-layer scaffold bridging multiple endonucleases with telomeres for recombination-based telomere maintenance

Inferring Group-Wise Consistent Multimodal Brain Networks via Multi-View Spectral Clustering

Quantitative modeling and analysis of structural and functional brain networks based on diffusion tensor imaging (DTI) and functional MRI (fMRI) data have received extensive interest recently. However, the regularity of these structural and functional brain networks across multiple neuroimaging modalities and also across different individuals is largely unknown. This paper presents a novel approach to inferring group-wise consistent brain sub-networks from multimodal DTI/resting-state fMRI datasets via multi-view spectral clustering of cortical networks, which were constructed upon our recently developed and validated large-scale cortical landmarks - DICCCOL (Dense Individualized and Common Connectivity-based Cortical Landmarks). We applied the algorithms on DTI data of 100 healthy young females and 50 healthy young males, obtained consistent multimodal brain networks within and across multiple groups, and further examined the functional roles of these networks. Our experimental results demonstrated that the derived brain networks have substantially improved inter-modality and inter-subject consistency

Detection of human influences on temperature seasonality from the 19th century

It has been widely reported that anthropogenic warming is detectable with high confidence after the 1950s. However, current palaeoclimate records suggest an earlier onset of industrial-era warming. Here, we combine observational data, multiproxy palaeo records and climate model simulations for a formal detection and attribution study. Instead of the traditional approach to the annual mean temperature change, we focus on changes in temperature seasonality (that is, the summer-minus-winter temperature difference) from the regional to whole Northern Hemisphere scales. We show that the detectable weakening of temperature seasonality, which started synchronously over the northern mid–high latitudes since the late nineteenth century, can be attributed to anthropogenic forcing. Increased greenhouse gas concentrations are the main contributors over northern high latitudes, while sulfate aerosols are the major contributors over northern mid-latitudes. A reduction in greenhouse gas emissions and air pollution is expected to mitigate the weakening of temperature seasonality and its potential ecological effects

Direct and indirect effects of climatic variations on the interannual variability in net ecosystem exchange across terrestrial ecosystems

Climatic variables not only directly affect the interannual variability (IAV) in net ecosystem exchange of CO2 (NEE) but also indirectly drive it by changing the physiological parameters. Identifying these direct and indirect paths can reveal the underlying mechanisms of carbon (C) dynamics. In this study, we applied a path analysis using flux data from 65 sites to quantify the direct and indirect climatic effects on IAV in NEE and to evaluate the potential relationships among the climatic variables and physiological parameters that represent physiology and phenology of ecosystems. We found that the maximum photosynthetic rate was the most important factor for the IAV in gross primary productivity (GPP), which was mainly induced by the variation in vapour pressure deficit. For ecosystem respiration (RE), the most important drivers were GPP and the reference respiratory rate. The biome type regulated the direct and indirect paths, with distinctive differences between forests and non-forests, evergreen needleleaf forests and deciduous broadleaf forests, and between grasslands and croplands. Different paths were also found among wet, moist and dry ecosystems. However, the climatic variables can only partly explain the IAV in physiological parameters, suggesting that the latter may also result from other biotic and disturbance factors. In addition, the climatic variables related to NEE were not necessarily the same as those related to GPP and RE, indicating the emerging difficulty encountered when studying the IAV in NEE. Overall, our results highlight the contribution of certain physiological parameters to the IAV in C fluxes and the importance of biome type and multi-year water conditions, which should receive more attention in future experimental and modelling research

DICCCOL: Dense Individualized and Common Connectivity-Based Cortical Landmarks

Is there a common structural and functional cortical architecture that can be quantitatively encoded and precisely reproduced across individuals and populations? This question is still largely unanswered due to the vast complexity, variability, and nonlinearity of the cerebral cortex. Here, we hypothesize that the common cortical architecture can be effectively represented by group-wise consistent structural fiber connections and take a novel data-driven approach to explore the cortical architecture. We report a dense and consistent map of 358 cortical landmarks, named Dense Individualized and Common Connectivity–based Cortical Landmarks (DICCCOLs). Each DICCCOL is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. Our results have shown that these 358 landmarks are remarkably reproducible over more than one hundred human brains and possess accurate intrinsically established structural and functional cross-subject correspondences validated by large-scale functional magnetic resonance imaging data. In particular, these 358 cortical landmarks can be accurately and efficiently predicted in a new single brain with DTI data. Thus, this set of 358 DICCCOL landmarks comprehensively encodes the common structural and functional cortical architectures, providing opportunities for many applications in brain science including mapping human brain connectomes, as demonstrated in this work