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Nitric oxide promotes cysteine N-degron proteolysis through control of oxygen availability
Selected proteins containing an N-terminal cysteine (Nt-Cys) are subjected to rapid, O 2 -dependent proteolysis via the Cys/Arg-branch of the N-degron pathway. Cysteine dioxygenation is catalyzed in mammalian cells by 2-aminoethanethiol dioxygenase (ADO), an enzyme that manifests extreme O 2 sensitivity. The canonical substrates of this pathway in mammalia are the regulators of G-protein signaling 4, 5, and 16, as well as interleukin-32. In addition to operating as an O 2 -sensing mechanism, this pathway has previously been described as a sensor of nitric oxide (NO), with robust effects on substrate stability upon modulation of NO bioavailability being widely demonstrated. Despite this, no mechanism to describe the action of NO on the Cys/Arg N-degron pathway has yet been substantiated. We demonstrate that NO can regulate the stability of Cys N-degron substrates indirectly via the regulation of ADO cosubstrate availability. Through competitive, O 2 -dependent inhibition of cytochrome C oxidase, NO can substantially modify cellular O 2 consumption rate and, in doing so, alter the availability of O 2 for Nt-Cys dioxygenation. We show that this increase in O 2 availability in response to NO exposure is sufficient to alter both dynamic and steady-state ADO substrate levels. It is likely that this mechanism operates to couple O 2 supply and mitochondrial respiration with responses to G-protein-coupled receptor stimulation.
Sustainable stabilization of microfluidized chia oil nanoemulsions by mixed proteins
Unraveling the neuroimmune mechanisms in cancer-induced bone pain: New horizons for therapeutic intervention of the two-phase paradigm
Cancer-induced bone pain (CIBP) is a severely painful condition that profoundly impacts patients’ quality of life. However, the neuroimmune mechanisms underlying CIBP remain largely elusive. Substance P (SP), which is known to play a pivotal role in pain perception, became the focal point of our study. To this end, we adopted a comprehensive approach combining behavioral and physiological methods to investigate its role in neuroimmune interactions in CIBP. The results showed that SP released by dorsal root ganglion (DRG) neurons via exocytosis initiates CIBP, with its release peaking on the 14th day and correlating with pain behavior. Macrophages were found to infiltrate the DRGs and the sciatic nerves. Notably, in mice with CIBP, the population of macrophage type I was significantly augmented. Significantly, we found that the deletion of macrophages led to a notable alleviation of CIBP, while the blockade of the SP-neurokinin 1 receptor pathway effectively mitigated the infiltration of macrophages and alleviated CIBP. In the advanced phase, DRGs released C-C Motif Chemokine Ligand 3 and C-C Motif Chemokine Ligand 2 to recruit macrophages. A two-phase model for CIBP progression in mice was proposed, with SP-induced macrophage infiltration in the primary phase and chemokine-mediated macrophage recruitment in the advanced phase. Our investigation has unearthed a previously unrecognized mechanism governing the neuroimmune interaction in CIBP, which highlights a critical target for impeding the progression of this debilitating pain, potentially opening up broad avenues for the development of effective therapeutic interventions at different stages of CIBP with cancer development.
Optimizing calcium efficiency for sustainable cement with GGBFS-fly ash systems
Loss of sialic acid side-chain <i>O</i> -acetylation exacerbates colitis
Sialic acids (Sias) are a diverse family of nine-carbon backbone monosaccharides occupying terminal positions on cell surface and secreted glycans and are abundant at mucosal surfaces. Sias can be modified with O -acetyl esters on the side chain (C7 to C9) hydroxyls. Structural analysis and functional studies of these modifications are challenging due to chemical lability and variable resistance to sialidases. For in-depth analysis of the expression and functions of O -acetyl Sia modifications, we used a unique set of sialoglycan-recognizing probes, HPLC analysis of DMB-derivatized Sias and mice lacking the first known sialate O -acetyltransferase, CASD1. C7/C9- O -acetylated Sias are most abundant in the colon, with lower levels in the heart, brain, and spleen, and minimal levels in other digestive organs of wild-type mice. CASD1 deficiency led to a marked loss of C9/C7- O -acetylated Sias in the colon and other tissues. No differences were observed in colonic O -acetylated Sias from conventional and germ-free wild-type mice, indicating that Sia O -acetylation is independent of the commensal microbiota. Nonetheless, CASD1 deficiency caused subtle changes in microbial gene repertoire consistent with potential exploitation of Sias by subsets of intestinal microbes. Furthermore, CASD1-deficient mice exhibited more severe inflammation and ulceration upon colitis induction compared to controls. Reduced Sia O -acetylation was observed in mice during acute colitis and in colon biopsies from patients with inflammatory bowel disease. Together, our findings suggest CASD1 is the primary physiologically relevant enzyme to add C7/C8/C9- O -acetyl ester groups to Sias and that these Sia modifications exert important gut-protective functions, perhaps by preventing microbial Sia release and metabolism.
Improved pulmonary embolism detection in CT pulmonary angiogram scans with hybrid vision transformers and deep learning techniques
Abstract Pulmonary embolism (PE) represents a severe, life-threatening cardiovascular condition and is notably the third leading cause of cardiovascular mortality, after myocardial infarction and stroke. This pathology occurs when blood clots obstruct the pulmonary arteries, impeding blood flow and oxygen exchange in the lungs. Prompt and accurate detection of PE is critical for appropriate clinical decision-making and patient survival. The complexity involved in interpreting medical images can often results misdiagnosis. However, recent advances in Deep Learning (DL) have substantially improved the capabilities of Computer-Aided Diagnosis (CAD) systems. Despite these advancements, existing single-model DL methods are limited when handling complex, diverse, and imbalanced medical imaging datasets. Addressing this gap, our research proposes an ensemble framework for classifying PE, capitalizing on the unique capabilities of ResNet50, DenseNet121, and Swin Transformer models. This ensemble method harnesses the complementary strengths of convolutional neural networks (CNNs) and vision transformers (ViTs), leading to improved prediction accuracy and model robustness. The proposed methodology includes a sophisticated preprocessing pipeline leveraging autoencoder (AE)-based dimensionality reduction, data augmentation to avoid overfitting, discrete wavelet transform (DWT) for multiscale feature extraction, and Sobel filtering for effective edge detection and noise reduction. The proposed model was rigorously evaluated using the public Radiological Society of North America (RSNA-STR) PE dataset, demonstrating remarkable performance metrics of 97.80% accuracy and a 0.99 for Area Under Receiver Operating Curve (AUROC). Comparative analysis demonstrated superior performance over state-of-the-art pre-trained models and recent ViT-based approaches, highlighting our method’s effectiveness in improving early PE detection and providing robust support for clinical decision-making.
A universal of speech timing: Intonation units form low-frequency rhythms
Intonation units (IUs) are a hypothesized universal building block of human speech [W. Chafe, Discourse, Consciousness and Time: The Flow and Displacement of Conscious Experience in Speaking and Writing (1994); N. P. Himmelmann et al. , Phonology 35 , 207–245 (2018)). Linguistic research suggests they are found across languages and that they fulfill important communicative functions such as the pacing of ideas in discourse and swift turn-taking. We study the rate of IUs in 48 languages from every continent and from 27 distinct language families. Using an analytic method to annotate natural speech recordings, we identify a low-frequency rate of IUs across the sample, with a peak at 0.6 Hz, and little variation between sexes or across the life span. We find that IU rate is only weakly related to speech rate quantified at the syllable level, and crucially, that cross-linguistic variation in IU rate does not stem from cross-linguistic variation in syllable rate.
Aging impairs type 2 immune responses to nematodes associated with reduced gut microbiota responsiveness
Summary Gastrointestinal nematode infections elicit robust type 2 immune responses that facilitate rapid parasite expulsion. Our previous studies demonstrated that 18-month-old mice exhibit both impaired nematode clearance and reduced type 2-cytokine production, suggesting that aging diminishes the host’s potential to mount effective immune defenses. To further investigate the underlying mechanisms, we compared young (3 months old) and aged mice (18 months old) infected with the nematode Heligmosomoides polygyrus (Hp), focusing on the interplay between type 2 immune responses and intestinal ecology. Hp infected young mice exhibited increased expression of Th2 cytokines (e.g., il-4) and short-chain fatty acid (SCFA) receptors GPR41/GPR43, while these responses were markedly diminished in aged mice. Correspondingly, cecal SCFA levels—particularly acetate and propionate—increased in Hp infected young mice but decreased in aged counterparts. Moreover, Hp infection induced a pronounced shift in the cecal microbiota composition of young mice, notably a reduced Bacillota/Bacteroidota ratio (F/B) ratio, a change much less evident in aged mice. These findings suggest that the age-related decline in type 2 immune responses to gastrointestinal nematode infection is linked to reduced gut microbiota responsiveness, which may compromise host resistance to the gastrointestinal parasites.
GATA3 promotes ferroptosis resistance by repressing integrin β1 signaling
Understanding mechanisms that determine the response of cells to ferroptotic stress is a timely issue that has significant ramifications for biology and pathology. We investigated these mechanisms in the context of breast cancer where tumors are composed of diverse populations of cancer cells that differ in their ferroptosis sensitivity. Using single-cell RNA-sequencing, we determined that cancer cell populations with luminal differentiation are more resistant to ferroptosis than other cells within a heterogeneous tumor. Subsequent bioinformatic analysis and experimentation revealed that GATA3, a transcription factor that promotes luminal differentiation, has a causal role in ferroptosis resistance in luminal breast cancer cells. In pursuit of the mechanism involved, we found that GATA3 represses the expression of integrin β1 and its downstream signaling cascade. This observation led us to demonstrate that integrin β1 signaling is necessary for sensitivity to ferroptosis in basal breast cancer cells because it regulates a FAK/ROCK pathway that sustains the expression of ACSL4, a lipid-modifying enzyme that is essential for ferroptosis. The repression of integrin β1 by GATA3 inhibits this signaling pathway, rendering cells ferroptosis resistant. Together, these data provide insight into mechanisms of ferroptosis sensitivity and resistance that are linked to the cell biology and signaling pathways of the diverse types of cells present in breast tumors.
Correction: RBM10 suppresses colorectal cancer invasion by regulating LncRNA SNHG17 alternative splicing
ER-resident CCDC134 safeguards TLR4 maturation by maintaining gp96 stability
Toll-like receptor 4 (TLR4), a pattern-recognition receptor located on the plasma membrane, senses extracellular danger signals to initiate inflammatory immune responses. It is initially synthesized in the endoplasmic reticulum (ER), undergoes N-linked glycosylation, and is subsequently transported to the Golgi before ultimately reaching the plasma membrane. However, the mechanisms underlying the processing and maturation of TLR4 in the ER remain elusive. Through whole genome-wide CRISPR screening, CCDC134 was identified as a critical and essential factor for TLR4-dependent inflammatory response. Localization of CCDC134 in the ER lumen rather than its exosome-mediated secretion is required for its role in TLR4 signaling. Loss of CCDC134 results in the retention of TLR4 in the ER for subsequent ER-associated degradation, and thus blockade of TLR4 maturation and plasma membrane trafficking. Defects in TLR4 processing and maturation in the ER in CCDC134-depleted cells are caused by aberrant hyperglycosylation and destabilization of glycoprotein 96 (gp96), a key chaperone of TLR4. These results suggest that CCDC134 controls gp96 glycosylation to facilitate TLR4 maturation in the ER.
Model-based partition scheduling of integrated modular avionics systems using genetic algorithm
Synergistic action of specialized metabolites from divergent biosynthesis in the human oral microbiome
Despite extensive efforts, our understanding of the virulence factors contributing to oral biofilm formation—a hallmark of dental caries—remains incomplete. We present evidence that the specialized metabolism of the oral microbiome is a critical yet underexplored factor in oral biofilm formation. Through microbiome analysis, we identified a hybrid nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) encoding biosynthetic gene cluster that correlates with dental caries and is widely represented in oral pathogens, including Streptococcus mutans . This gene cluster produces two major mutanoclumpin metabolites, MC-584 and MC-586, which feature molecular scaffolds differing in a C–C macrocyclic linkage. Both metabolites synergistically promote robust biofilm formation of S. mutans through a rare dual-metabolite mode of action. Further, each metabolite binds uniquely to the S. mutans cell surface, resulting in distinct multicellular morphologies. The biosynthesis of mutanoclumpins employs a unique chemical logic that produces two major products, rare within PKS-NRPS assembly lines. This study underscores the importance of characterizing genes implicated in human diseases through microbiome analysis and lays the foundation for exploring strategies to inhibit streptococci-induced dental caries.
Co-administration of low-dose-Naltrexone and Carbamazepine remarkedly ameliorate allodynia and cognitive deficit in a rat model of trigeminal neuralgia
Sparse autoencoders uncover biologically interpretable features in protein language model representations
Foundation models in biology—particularly protein language models (PLMs)—have enabled ground-breaking predictions in protein structure, function, and beyond. However, the “black-box” nature of these representations limits transparency and explainability, posing challenges for human–AI collaboration and leaving open questions about their human-interpretable features. Here, we leverage sparse autoencoders (SAEs) and a variant, transcoders, from natural language processing to extract, in a completely unsupervised fashion, interpretable sparse features present in both protein-level and amino acid (AA)-level representations from ESM2, a popular PLM. Unlike other approaches such as training probes for features, the extraction of features by the SAE is performed without any supervision. We find that many sparse features extracted from SAEs trained on protein-level representations are tightly associated with Gene Ontology (GO) terms across all levels of the GO hierarchy. We also use Anthropic’s Claude to automate the interpretation of sparse features for both protein-level and AA-level representations and find that many of these features correspond to specific protein families and functions such as the NAD Kinase, IUNH, and the PTH family, as well as proteins involved in methyltransferase activity and in olfactory and gustatory sensory perception. We show that sparse features are more interpretable than ESM2 neurons across all our trained SAEs and transcoders. These findings demonstrate that SAEs offer a promising unsupervised approach for disentangling biologically relevant information present in PLM representations, thus aiding interpretability. This work opens the door to safety, trust, and explainability of PLMs and their applications, and paves the way to extracting meaningful biological insights across increasingly powerful models in the life sciences.
How ESG accelerates the industrial robot applications in manufacturing
Melanocyte-dependent macrophage redistribution enhances skin immunity upon acute stress
It is well established that stress generally suppresses immunity. However, under certain conditions, acute stress has been shown to stimulate the immune system, particularly those at barrier surfaces like the skin. The cellular and molecular mechanisms underlying this effect remain poorly understood. In the present study, we have identified an immune-enhancing effect of stress using zebrafish larvae. The use of this animal model allowed us to visualize the redistribution of macrophages to the skin upon exposure to an acute stressor, which appeared to be dependent on the increased levels of cortisol. Through real-time imaging of fluorescently labeled leukocytes, we observed that this cortisol-driven redistribution was mediated by both the mineralocorticoid and the glucocorticoid receptor, which upregulated the chemokine receptor Cxcr4. Strikingly, this stress-induced macrophage migration required the presence of melanocytes in the skin, which increased the expression of the gene encoding Cxcl12, the ligand for Cxcr4. This result indicates a pivotal role for pigment cells in immune regulation under stress. Functional assays further revealed that the redistributed macrophages actively increased antigen uptake from the external environment, suggesting an elevated state of immune readiness. Together, we demonstrate that acute stress triggers a coordinated, cortisol-mediated response that enhances immune surveillance at the skin barrier. This stress-induced enhancement of barrier immunity potentially prepares the organism for increased pathogen exposure under challenging conditions.
The role of traditional ecological knowledge and ecosystem quality in managing ecosystem services
Aspartic acid residues in BBE-like enzymes from <i>Morus alba</i> promote a function shift from oxidative cyclization to dehydrogenation
Berberine bridge enzyme (BBE)-like enzymes catalyze various oxidative cyclization and dehydrogenation reactions in natural product biosynthesis, but the molecular mechanism underlying the selectivity remains unknown. Here, we elucidated the catalytic mechanism of BBE-like oxidases from Morus alba involved in the oxidative cyclization and dehydrogenation of moracin C. X-ray crystal structures of a functionally promiscuous flavin adenine dinucleotide (FAD)–bound oxidase, MaDS1, with and without an oxidative dehydrogenation product were determined at 2.03 Å and 2.21 Å resolution, respectively. Structure-guided mutagenesis and sequence analysis have identified a conserved aspartic acid that directs the reaction toward the oxidative dehydrogenation pathway. A combination of density functional theory (DFT) calculations and molecular dynamics (MD) simulations has revealed that aspartic acid acts as the catalytic base to deprotonate the carbon-cation intermediate to generate the dehydrogenated product, which otherwise undergoes a spontaneous 6π electrocyclization in the oxidative cyclization pathway to furnish the 2H-benzopyran product.