Museums and public collections often contain archaeological clay artifacts of unknown origin. Such artifacts, if proven to be authentic, may contribute significantly to our understanding of ancient societies. However, the authenticity of these artifacts is usually highly debated, resulting in their being disregarded in historical interpretations. Several laboratory methods have been developed in order to authenticate such objects but none have been proven infallible. Here we present a method for distinguishing between authentic and fake clay artifacts by considering the Viscous Remanent Magnetization (VRM) acquired by the artifacts. Clay objects tend to acquire a strong magnetic signal termed Thermal Remanent Magnetization (TRM) upon heating and cooling in kilns during their manufacturing process. After being removed from the orientation in which their TRM was acquired, these objects were exposed to an ambient geomagnetic field in a different direction. Over archaeological time scales, this results in the acquisition of a significant VRM. We propose a laboratory protocol for identifying this ancient VRM. We validated the protocol using micromagnetic modeling of single domain particles and by laboratory experiments carried out on 19 ancient and 26 modern objects, made from different types of clay and fired using different firing techniques. Both the experiments and the simulations indicate that the existence of a significant VRM component removed at temperatures higher than a cutoff temperature of [Formula: see text]C is indicative of ancient objects while its removal at lower temperatures is indicative of modern objects. We successfully applied this method to objects of debated authenticity.
Lenacapavir (LEN), a potent capsid inhibitor, suppresses reverse transcription and nuclear import by disrupting capsid core formation in HIV type 1 (HIV-1). However, its effects on late-stage viral assembly remain unclear. Although p24 ELISA suggested that LEN substantially inhibited HIV-1, both RT-dPCR and Vpr-HiBiT assays indicated that suppression of viral release required relatively high LEN concentrations. This discrepancy was attributed to LEN-induced reduction in p24 solubility, leading to an overestimation of its inhibitory effect on viral release. In addition, excessive intracellular Gag processing by the viral protease was observed in the presence of LEN, which contributed to impaired viral release. Furthermore, LEN induced numerous abnormal, discrete clusters of Gag at the plasma membrane. Using mass photometry, which was applied to analyze HIV-1 particle sizes, and transmission electron microscopy, we identified heterogeneous LEN-induced viral-like particles (LENiVLPs; diameter >200 nm) containing both Gag and Env proteins. Although LENiVLPs retained membrane fusion capability, they were noninfectious owing to postentry defects that prevented viral replication. Thus, LEN binds to the precursor Gag and promotes aberrant particle formation, offering insights that could guide the development of next-generation LEN-based therapeutics targeting the late stages of the viral life cycle.
Antimicrobial resistance (AMR) is a growing One Health challenge, and as climate warming intensifies extreme events, it remains unclear how these disturbances affect soil antibiotic resistance genes (ARGs). Here we analyzed the data from a controlled experiment using soils from 30 grassland sites across ten European countries, which simulated drought, flooding, freeze-thaw, and heatwaves to explore ARG dynamics. Overall, ARGs exhibited relatively small but highly consistent shifts across treatments. Heatwaves caused the strongest reductions in ARG abundance and in their linkages with mobile genetic elements (MGEs), a pattern that may reflect a hypothesized metabolic-genetic trade-off, in which microbial investment may shift from core metabolism toward stress signaling and structural maintenance. ARG dynamics during and after disturbance were governed by distinct soil physicochemical properties, with temperature and nutrient status determining acute responses, whereas soil moisture and seasonal variability in temperature and precipitation shaped longer-term legacy effects. Cross-validated random-forest models showed positive predictive performance for Bray-Curtis-based compositional responses within the environmental range represented by the 30 grassland sites. Our findings enhance the understanding of how soil ARGs respond to extreme climatic events and provide a step toward predicting extreme-event impacts on soil resistomes with relevance to One Health.
In aquatic environments, gradients in flow velocity and turbulence define a constantly shifting landscape that sets the physical constraints on propulsion and energy expenditure in fish. Successfully navigating these complex flows depends on the ability to sense and respond to subtle hydrodynamic cues in an energy-efficient manner. Revealing these mechanisms is central to understanding how fish identify and exploit favorable flow conditions. To this end, we designed a hydrodynamic maze with spatially varying mean flow and turbulence, creating a controlled heterogeneous flow landscape for understanding fish movement strategies. We found that fish escape energetically unfavorable regions by yawing their bodies relative to the flow. These yawed orientations appear to facilitate lateral migration through lift forces and may improve sensitivity to local flow variations. Notably, fish maintain body orientations near, but below, predicted stall conditions to exploit lift without a significant increase in drag. These findings provide insight into how fish navigate heterogeneous hydrodynamic environments, with potential relevance for both natural and engineered flow systems.
We introduce GenAI-Powered Inference (GPI), a statistical framework for causal inference using unstructured data, including text and images. GPI leverages open-source pretrained Generative AI (GenAI) models-such as large language models and diffusion models-not only to generate unstructured data at scale but also to extract low-dimensional representations that are guaranteed to capture their underlying structure. Applying machine learning to these representations, GPI enables estimation of causal effects while quantifying estimation uncertainty. Unlike existing approaches to representation learning, GPI does not require fine-tuning of GenAI models, making it computationally efficient and broadly accessible. We illustrate the versatility of the GPI framework through three applications: 1) estimating the effects of Chinese social media censorship while adjusting for textual confounders, 2) isolating the impact of specific image features from that of other correlated features in the same image, and 3) assessing the persuasiveness of political rhetoric. An open-source software package is available for implementing GPI.
Protein posttranslational modifications (PTMs) play a central role for regulating protein function and cellular processes, with many PTMs arising from reactions with electrophilic metabolites. Here we extend the known landscape of PTMs with the identification of “lysine C 3 -iminylation,” the conjugation of protein lysine residues with propionaldehyde. To stabilize iminylation for mass spectrometric analyses and distinguish it from other isomeric PTMs, we developed a fixation and stable-isotope labeling approach based on parallel reduction of proteome with sodium borohydride and borodeuteride. Analyses of protein hydrolysates confirmed the presence of C 3 -iminylation in Caenorhabditis elegans and mouse. Additionally, proteomics results demonstrated specificity of this PTM in vitro and in vivo and revealed C 3 -iminylation in proteins related to critical metabolic pathways. Importantly, collective evidence from isotope tracing as well as genetic, dietary, and pharmacological manipulation experiments uncovered that C 3 -iminylation originates from cytochrome P450 (CYP)-mediated oxidation of omega-3 fatty acids. Correspondingly, C 3 -iminylation levels were elevated in C. elegans daf-2 ( e1370 ) mutants, an aging model, in which CYP activity is generally increased. These findings not only expand our understanding of the biochemical diversity of PTMs but also underscore the complex interplay between lipid metabolism and protein modifications, enabling further exploration of their biological and clinical implications.
Only a subset of heroin users develop addiction, characterized by binge-like heroin use and preference for heroin over other rewards, including social rewards. We recently established a rat model that captures these features. We trained rats to lever-press for social interaction and heroin (or saline, control) infusions and then tested heroin and social seeking and heroin-vs.-social choice. During 3 to 5 abstinence weeks, we used 2-deoxy-2-[ 18 F]fluoro-D-glucose (FDG) positron emission tomography (PET) imaging to assess regional brain metabolic activity at rest (homecage) and during heroin and social seeking. We assessed regional differences in FDG uptake using unbiased voxel-wise analysis and statistical parametric mapping, and correlated FDG uptake with principle-component-analysis-derived addiction severity score incorporating heroin intake, binge-like episodes, and heroin preference. Compared with saline-trained rats, heroin-trained rats showed overall higher FDG uptake across multiple brain regions at rest and during both reward-seeking tests. Comparison of heroin-vs.-social-seeking in heroin-trained rats showed higher uptake in claustrum/striatum and auditory cortex during social seeking. Analysis of individual differences showed that addiction severity was primarily associated with metabolic alterations under resting conditions rather than during heroin or social seeking. At rest, higher addiction severity was associated with lower uptake in piriform cortex and higher uptake in ventral hippocampus, whereas during heroin seeking, addiction severity was associated with lower uptake in postsubiculum and cerebellum. Addiction severity was not associated with differences in social measures or FDG uptake during social-seeking. These findings identify brain metabolic features of heroin addiction vulnerability in a rat model that may serve as brain biomarkers of human opioid addiction.
The absence of input from one sense can lead to a greater emphasis on the remaining senses, resulting in heightened performance. Numerous behavioral studies demonstrate that adults who have been deaf from an early age have superior visual sensitivity, particularly to far-peripheral stimuli. We asked whether the increased demand on peripheral vision throughout development that comes with early, profound deafness might be reflected in changes in early visual brain structures. Using functional MRI, we mapped visual field representations in 16 early, profoundly D/deaf adults and 16 hearing age-matched controls. D/deaf individuals exhibited a larger representation of the far-peripheral visual field in both the primary visual cortex and the lateral geniculate nucleus of the thalamus. Importantly, this was not due to a total expansion of the visual map, as there was no difference between groups in overall size of either structure, but a smaller representation of the central visual field in the D/deaf group, suggesting a redistribution of neural resources. Here, we demonstrate that the demands placed on vision due to lifelong deafness can sculpt first level visual map input, to increase neural processing resources for far-peripheral visual stimuli.
We have previously shown that a T cell engaging bispecific humanized anti-human EpCAM-CD3 antibody efficiently kills a human EpCAM positive human xenograft in an NSG partially humanized mouse injected intravenously with human T cells when the anti-EpCAM-CD3 was delivered intratumorally as an mRNA-LNP. To extend these results we tested the effects of combining the anti-human EpCAM-CD3 with various cytokines injected into a tumor on the left side of NSG mice and an uninjected tumor on the right side of the mice. Combining both IL-12 and GM-CSF with anti-EpCAM-CD3 increased the number of T cells and the expression of genes and pathways that mediated T cell-based killing in the neighborhood of both the injected and the uninjected tumor and substantial increases in the expression of HLA Class II and associated genes in both tumors. This turned the cancer cells into potentially antigen-presenting cells. The effect of combining intratumoral injection of anti-EpCAM-CD3 with cytokines IL-12 and GM-CSF on tumor growth distal to the injection site avoids serious side effects on normal tissue, and suggests this technology offers a major approach to immunotherapy for treatment of a wide range of cancers from early to severe late stages.
Repeated divergence across contrasting habitats is widely used to infer natural selection and adaptation. Such comparative inferences, however, remain inherently correlative and capture only adaptation shared among populations from the same habitat type, thereby missing site-specific adaptation unique to individual populations. Field transplant experiments test adaptation directly by measuring fitness in nature but are typically limited to pairwise reciprocal exchanges between populations and therefore cannot distinguish between habitat-level and site-specific adaptation. Here, we extend the typical transplant framework to include multiple populations from both within and across habitat types, allowing fitness variation to be partitioned into shared habitat-level and unique site-specific components. We apply this framework to lake-stream stickleback, a classic system for studying adaptation via repeated divergence. Specifically, we transplanted laboratory-reared fish from a panmictic lake population and four independent stream populations across one lake and two stream sites. Stream fish outperformed lake fish in streams and vice versa, demonstrating adaptive divergence across the lake-stream divide. However, at both stream sites, local stream fish also outperformed foreign stream fish. Strikingly, this site-specific advantage was twice as large as the advantage of shared stream adaptation reflected by the fitness benefit of foreign stream fish over foreign lake fish. These results show that most fitness-relevant evolutionary variation in this system is unique to individual populations and therefore invisible to approaches that rely on repeated evolution to infer adaptation. More broadly, our work underscores the importance of ecological scale for understanding adaptation and evolutionary predictability.
Foreign information manipulation and interference (FIMI) is an important part of the digital information ecosystem, yet its effects are poorly understood. Most research analyzing FIMI to date is descriptive, exposing efforts to erode trust, promote favorable narratives, and target specific communities. Existing work evaluating the impacts of FIMI contrasts those directly exposed to FIMI messaging (by viewing the original messages) with those who were not, finding little evidence of changes in beliefs or behavior. Rather than persuading individuals directly, we argue FIMI often operates through agenda-setting processes that shape which issues and narratives dominate public discourse. A key component of this process is narrative laundering, whereby misleading content is scrubbed of its origins and circulated into mainstream channels. This study examines the Russian-aligned Storm-1516 campaign, which uses state media, fabricated sites, and paid influencers to elevate false narratives, especially those that implicate Ukrainian President Volodymyr Zelenskyy in corrupt acts. By analyzing the dissemination of these narratives, we assess how Storm-1516 shifts the public agenda, illustrating how foreign influence can exert substantial effects on information environments even when individual-level persuasive effects may be limited.
Protein structure search has been revolutionized by deep learning methods that can rapidly search massive databases. However, current structure search tools often miss proteins related by topological rearrangements, particularly circular permutation, wherein proteins share highly similar structure but differ in the positioning of their termini. We introduce a circular permutation-invariant graph neural network (CIRPIN) that addresses this limitation through a data augmentation strategy using synthetic circular permutations. We demonstrate that CIRPIN learns representations of proteins that are invariant to circular permutation, enabling it to identify structurally similar proteins within the Structural Classification of Proteins and AlphaFold Cluster Representatives databases. Using CIRPIN, we created CIRPIN-DB, a database of 18.3 million protein pairs highly enriched for circular permutation relationships. Our database contains structures from 845 unique topologies in the CATH Protein Structure Classification database representing the largest and most comprehensive resource of proteins related by a circular permutation assembled to date. Notably, among several novel circular permutants, we find that the PDZ domain—the most commonly inserted domain within multidomain proteins—exists in four distinct circularly permuted forms. Our results establish CIRPIN as a powerful tool to investigate the evolutionary mechanisms underlying circularly permuted proteins.
Celiac disease (CeD) and rheumatoid arthritis (RA) share several key features. In both diseases HLA class II allotypes are the major genetic determinants, in both diseases there are antibodies to posttranslationally modified peptides (i.e., deamidated peptides in CeD and citrullinated peptides in RA) and in both diseases there are autoantibodies to enzymes that mediate these peptide modifications (i.e., transglutaminase 2 for CeD and peptidyl arginine deiminase 2 and 4 for RA). In CeD, recent insights obtained from studies of antigen-specific immune cells have established a mechanistic model that integrates these key features by a pivotal involvement of enzyme-substrate complexes. Conceivably, the pathomechanism of RA parallels that of CeD in which autoreactive B cells by internalizing enzyme-substrate complexes present posttranslationally modified peptides to CD4+ T cells. This pathomechanism places enzyme-reactive B cells in the center of events. This notion resonates well with B cell depleting therapies being successfully explored for RA. A shared pathomechanism raises the possibility that RA, like exogenous cereal gluten proteins drive immunopathology in CeD, is driven by T cell reactions to foreign antigen.
The search for life beyond Earth has focused on planets and moons with liquid water, reflecting the assumption that complex biomolecules require aqueous environments to remain stable and functional. Such a view excludes a wide class of planetary settings, including the concentrated sulfuric acid clouds of Venus, where extreme acidity and minimal water are thought to preclude molecular structure despite suitable temperatures. A growing body of evidence shows that a wide range of organic molecules can remain stable in concentrated sulfuric acid, including nucleic acid bases, amino acids, lipid micelles and vesicles, and peptide nucleic acid (PNA), but such stability does not address whether macromolecules can retain folded structures required for function. Using NMR spectroscopy, here we show that three peptides adopt stable, well-defined folded structures in concentrated (98% w/w) sulfuric acid, an extreme solvent environment that has been long assumed to be incompatible with biomolecules. The peptides form compact Ω-loop conformations stabilized by solvent-mediated interactions and intramolecular hydrogen bonding. This finding strongly counters conventional thinking where sulfuric acid would destroy peptide bonds via acid-catalyzed hydrolysis. Here, the near absence of water in 98% (w/w) sulfuric acid means hydrolysis does not occur. The result identifies a regime in which macromolecular structure persists under conditions long considered incompatible with life. The finding expands the range of planetary environments that may support complex chemistry and motivates renewed consideration of chemically diverse exoplanets in the search for signs of life beyond Earth.
Tumor-suppressive immunity is more evident in early-stage compared to advanced tumors making it the ideal point for cancer interceptive immunotherapies. We previously described that higher peripheral T cell diversity is associated with more pronounced CD8 + T cell infiltration in ductal carcinoma in situ of the breast, implying a close interaction between peripheral and intratumor immunity. Here, we developed lipid nanoparticle (LNP)-encapsulated messenger ribonucleic acid (mRNA) vaccines expressing the alpha-lactalbumin (LALBA) protein unique to mammary luminal progenitors (LPs) to test whether enhancing immune response by prophylactic vaccination against the putative cell-of-origin of breast cancer suppresses tumorigenesis. Vaccination of outbred Sprague-Dawley rats with N1-methylpseudouridine-modified or unmodified Lalba mRNA-LNP induced different degrees of LALBA-specific and nonspecific immune responses. The vaccination suppressed carcinogen-induced mammary tumorigenesis and improved tumor-free and overall survival without obvious toxicity in the normal mammary glands and other organs. Single-cell transcriptomic analysis revealed that vaccination decreases the frequency of a proliferative LP population in immunoreactive early epithelial hyperplasia. Overall, we provide proof of principle that prophylactic Lalba mRNA-LNP has the potential to suppress the initiation and progression of early breast neoplastic lesions.
An RNA polymerase identified in the genome of Pseudomonas phage Njord offers a promising tool for the synthesis of mRNA and other therapeutic nucleic acids. Originating from a marine microbial ecosystem, Njord RNAP transcribes RNA at high yield even under low temperature conditions. Key properties of the enzyme relevant to mRNA synthesis are presented including transcriptional fidelity, promoter specificity, incorporation of modified nucleotides, and the impurity profile of the RNA. Specific attention is given to the formation of contaminating double-stranded RNA (dsRNA) species. Analysis of transcription reactions shows that DNA-templated promoter-independent transcription is a major source of detectable dsRNA impurities and that Njord RNAP displays a minimal level of this activity. Consistent with the known inflammatory role of dsRNA in synthetic mRNA, transcriptomic analysis of cell culture and a live animal study demonstrates that mRNA synthesized with Njord RNAP elicits only a minimal immune response. This natural enzyme enables efficient mRNA synthesis at ambient temperature and produces transcripts essentially free of dsRNA, offering significant potential to streamline mRNA manufacturing processes.
We demonstrate an approach to three-dimensional (3D) printing of ice structures by exploiting evaporative cooling. A micrometer-sized water jet is used to 3D print inside a vacuum chamber. The reduced ambient pressure leads to rapid evaporation of the extruded water, extracting latent heat, and quickly cooling the water well below 0 °C. Once deposited, the water freezes almost instantaneously into stable ice structures. We achieved high-fidelity printing via two distinct deposition techniques: layer-by-layer deposition for intricate 3D structures (e.g., a Christmas tree), and support-free mid-air printing for upright profiles (e.g., an in profile face), all achieved without cryogenic infrastructure, supporting materials, or external refrigeration. This approach directly visualizes fundamental thermodynamic principles—latent heat, evaporative cooling, and pressure-dependent phase transitions—while offering a relatively simple and scalable platform for ice-templated microfluidics and tissue engineering, or even extraterrestrial 3D printing.
Pancreatic ductal adenocarcinoma (PDAC) is characterized by a heavily fibrotic tumor microenvironment (TME), primarily driven by cancer-associated fibroblasts (CAFs). Due to the high heterogeneity and diverse biological behaviors of CAFs, the current strategies targeting CAFs have limited benefits in clinic. This study identifies a subset of CAFs marked by high expression of connective tissue growth factor (CTGF), which enhances tumor cell migration and correlates with advanced PDAC stages. By combining in silico screening and functional assays, we identified DP as a first-in-class small-molecule inhibitor targeting CTGF. Structural optimization of DP led to the synthesis of a series of derivatives, from which the optimal compound QX03-46 was identified. Targeting CTGF + CAFs with QX03-46 significantly disrupted the CTGF/TGF-β1 signaling axis and suppressed CAF functions, resulting in decreased extracellular matrix deposition and oncogenic cytokine secretion. Furthermore, it enhanced the efficacy of anti-programmed cell death ligand 1 therapy, promoting a more favorable immune response. Our findings illuminate the critical role of CTGF + CAFs in PDAC progression and position QX03-46 as a promising therapeutic candidate for targeting the fibrotic TME.
Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment in the aging population globally. Although genome-wide association studies (GWAS) have identified many AMD susceptibility loci, the genes and mechanisms underlying many of these associations remain unresolved. Here, we integrated expression quantitative trait locus (eQTL) data with AMD GWAS to prioritize nine putative genes. Through in vivo screening in zebrafish, we demonstrated that the downregulation of cnn2 and sarm1 expression led to ocular structural abnormalities and visual functional impairment. Subsequent mouse model studies confirmed that Cnn2 deficiency affected photoreceptor structure and function, impaired contrast sensitivity, and caused abnormalities in cone cell immunostaining. Given that CNN2 is predominantly expressed in endothelial cells, we propose that endothelial dysfunction may cascade to impair photoreceptor function. Collectively, through in silico prioritization and cross-species functional characterization, we identify CNN2 as a candidate susceptibility gene in AMD pathogenesis, providing vital underlying mechanistic insights.
