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Cryo-EM structure of the full-length LGR4-RSPOs complex and a targeting nanobody for anti-obesity therapy
Mammoth challenge: why we called our de-extinction company Colossal Biosciences
Injectable therapeutic system incorporating neurogenesis-programmed stem cells concomitantly promoting muscle regeneration treats stress urinary incontinence
Abstract Stress urinary incontinence (SUI) remains a significant clinical challenge due to the lack of strategies that simultaneously address muscle degeneration, neurogenic atrophy, and vascular deficits. Here, we report an innovative injectable system that combines a thermo-responsive poly(N-isopropylacrylamide)-COOH/leucine/decellularized extracellular matrix hydrogel with adipose-derived stem cells (ADSCs) pre-programmed by zeolitic imidazolate framework-8/polyethylene glycol 200@magnesium (ZIF-8/PEG200@Mg) nanoparticles. In vitro, programmed ADSCs exhibit enhanced neurogenic differentiation, while the hydrogels support robust myogenic activity and cell viability. In a female rat model of SUI—chosen to reflect the higher prevalence of SUI in women—the composite system leads to a marked improvement in leak point pressure (LPP) and restores urethral sphincter function. Mechanistic analyses reveals upregulation of muscle regeneration (e.g., Myoz1, Smyd1) and neurogenesis/neuromuscular junction stabilization (NMJ) stabilization genes (e.g., Dok7, Musk), highlighting a coordinated multi-lineage regenerative process. This work establishes an integrated regeneration-plus-support injectable strategy, offering a regenerative medicine-based approach that surpasses conventional bulking or sling therapies for SUI.
A chelate to break diffusion limits on Helmholtz plane for CO2 electroreduction to ethanol
Graph neural networks learn emergent tissue properties from spatial molecular profiles
Abstract Tissue phenotypes, such as metabolic states, inflammation, and tumor properties, emerge from both molecular states and spatial cell organization. Spatial molecular assays provide an unbiased view of tissue architecture, enabling phenotype prediction. Graph neural networks (GNNs) offer a natural framework for analyzing spatial proteomics by integrating expression profiles with structure. We apply GNNs to classify tissue phenotypes using spatial cell patterns. We show that for relatively simple classification tasks, such as tumor grading in breast cancer, incorporating spatial context does not significantly improve predictive performance over models trained on single-cell or pseudobulk representations. However, GNNs capture meaningful spatial features, retaining prognostic signals beyond tumor labels, highlighting tumor-grade-specific cell type interactions, and uncovering complex immune infiltration patterns in colorectal cancer not detectable with traditional approaches. These findings suggest that while spatial dependencies may not always enhance classification performance in small datasets, GNNs remain valuable tools for characterizing tissue organization and interactions.
Buffer optimization of siRNA-lipid nanoparticles mitigates lipid oxidation and RNA-lipid adduct formation
Abstract Lipid nanoparticles are a versatile class of clinically approved drug delivery vehicles, particularly for nucleic acid cargoes. Despite this, these materials often suffer from instability issues that limit shelf-life or necessitate storage at ultra-cold temperatures. Herein, we demonstrate that the oxidation of unsaturated hydrocarbons within ionizable lipid tails results in the production of a dienone species that changes the conformation of the lipid tail and generates an electrophilic degradant that reacts with neighboring siRNA cargoes to produce siRNA-lipid adducts. This mechanism highlights the interplay between lipid degradation, colloidal instability, RNA-lipid adduct formation, and loss of bioactivity. In this work, we show that revised drug product matrixes, including mildly acidic, histidine-containing formulations, can improve room temperature stability of siRNA-lipid nanoparticles by mitigating these oxidative degradation mechanisms.
Supramolecular chirality largely modulates chemical doping of conjugated polymers
Python, the movie! The programming language’s origin story comes to the silver screen
Enantioselective intramolecular cyclopropanation via a cationic sulfoxonium-Rh-carbene
Why is autism really on the rise? What the science says
Large lithium-ion battery model for secure shared electric bike battery in smart cities
When life gets in the way of your meticulously-planned career in science
Head start: fossil clues about how bodies evolved from two-fold to five-fold symmetry
TEtrimmer: a tool to automate the manual curation of transposable elements
Abstract Transposable elements (TEs) are repetitive DNA sequences that move within genomes and play important roles in gene regulation and genome evolution. Accurate TE annotation in genomes is crucial for downstream analyses but challenging due to their sequence diversity and frequent fragmentation, including the occurrence of nested copies. We here present TEtrimmer, a tool that automates and replaces key steps of traditional manual curation of TEs. TEtrimmer combines phylogenetic tree analysis with the machine learning method DBSCAN to cluster TE sequences accurately and applies a sliding-window strategy to remove poorly conserved regions of TE-derived multiple sequence alignments. TEtrimmer also provides detailed report plots and features a graphical user interface (GUI) application. Tested on the genomes of six organisms belonging to various kingdoms of eukaryotic life and three simulated genomes, TEtrimmer consistently improved the identification of intact TEs compared to the established tools EDTA and RepeatModeler2.
Predicting rhizosphere-competence-related catabolic gene clusters in plant-associated bacteria with rhizoSMASH
Abstract Plants release a substantial fraction of their photosynthesized carbon into the rhizosphere as root exudates that drive microbiome assembly. Deciphering how plants modulate the composition and activities of rhizosphere microbiota through root exudates is challenging, as no dedicated computational methods exist to systematically identify microbial root exudate catabolic pathways. Here, we integrate published information on catabolic genes in bacteria that contribute to their rhizosphere competence and develop the rhizoSMASH algorithm for genome-synteny-based annotation of rhizosphere-competence-related catabolic gene clusters (rCGCs) in bacteria with 58 curated detection rules. Our analysis reveals heterogeneity in rCGC prevalence both across and within plant-associated bacterial taxa, indicating extensive niche specialization. Furthermore, we demonstrate the predictive value of the presence or absence of rCGCs for rhizosphere competence in machine learning with two case studies. rhizoSMASH provides an extensible framework for studying rhizosphere bacterial catabolism, facilitating microbiome-assisted breeding approaches for sustainable agriculture.
Stabilizing buried interface by bilateral bond strength equilibrium strategy toward efficient perovskite photovoltaics
Active learning accelerates electrolyte solvent screening for anode-free lithium metal batteries
Replay and representation dynamics in the hippocampus of freely flying bats
Abstract Cognitive functions for navigation and memory rely on emergent properties of neural ensembles in the hippocampus, such as activity replay1–5 and theta sequences6–9. However, whether and how these phenomena generalize across species with distinct navigational demands and neurophysiological properties remains unclear. Here we wirelessly recorded neural activity from large populations of cells and local field potentials from the hippocampus of freely flying Egyptian fruit bats (Rousettus aegyptiacus) engaged in free, spontaneous foraging behaviour. During rest, we identified time-compressed forward and reverse replays of multiple flight trajectories coinciding with sharp-wave ripples. Notably, replays occurred predominantly at locations that were both spatially and temporally distant from the replayed behaviour, and their speed scaled with trajectory length, challenging present models of replay mechanisms. During flight, neural ensembles exhibited fast representational sweeps, in which the decoded location moved ahead of the bat’s position cyclically. In contrast to reports in rodents, sweeps occurred in the absence of theta oscillations, and were instead phase locked to a prominent motor behavioural rhythm—the bat’s wing-beat cycle. This suggests that behaviourally relevant sensorimotor rhythms can interact with hippocampal ensemble dynamics in a highly structured manner. Combined, our findings challenge existing models of ensemble dynamics in the mammalian hippocampus, and highlight the importance of comparative studies in ethologically relevant conditions for elucidating brain function.
Slab Grave expansion disrupted long co-existence of distinct Bronze Age herders in central Mongolia
Abstract Dairy pastoralism reached Mongolia during the Early Bronze Age and flourished in the Late Bronze Age alongside the emergence of diverse mortuary practices, including the Deer Stone-Khirgisuur Complex and figure-shaped/Ulaanzuukh burials. While the spread of pastoralism has been widely studied, interactions between these pastoralist groups with distinct mortuary traditions remain underexplored due to challenges in obtaining both genomic and mortuary data. In this study, we analyzed genome-wide and mortuary data from 30 ancient individuals in central Mongolia, a key region where pastoralists with distinct mortuary practices converged. We identify two genetically distinct clusters persisting throughout the Late Bronze Age that correspond to separate burial types, suggesting limited genetic mixing and a maintenance of distinct mortuary practices despite their coexistence. These groups were eventually replaced during the Early Iron Age by the expansion of the Slab Grave population and the establishment of a new burial tradition. Finally, we refine the genetic origin of the Late Bronze Age Deer Stone-Khirgisuur Complex populations, tracing their minor western Eurasian ancestry back to the Eneolithic/Early Bronze Age Afanasievo and Early Bronze Age Khemtseg (Chemurchek) populations. This study provides fine-scaled genetic tracking of major mortuary transitions in prehistoric Mongolia, offering insights into the complex and divergent processes that shaped the ancient pastoralist societies of Asia.