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Target identification and assessment in the era of AI
A cooperative effect of ligands, Mg2+ ions, and the U6C mutation on the structural dynamics of the SAM-Ⅵ Riboswitch
De novo EHMT2 variants cause an autosomal dominant EHMT2-related Kleefstra syndrome via loss of G9a methyltransferase activity
Abstract EHMT1 and EHMT2 genes encode human euchromatin histone lysine methyltransferase 1 and 2 (EHMT1 alias GLP; EHMT2 alias G9a) that form heteromeric GLP/G9a complexes with essential roles in epigenetic regulation of gene expression. While EHMT1 haploinsufficiency has been established as the cause of Kleefstra syndrome 1, the pathogenesis of G9a dysfunction in human disease remains largely unknown. We identified seven de novo EHMT2 variants in patients with clinical presentation, episignatures, histone modifications and transcriptomic profiles similar to those of Kleefstra syndrome 1. In vitro studies reveal that these variants encode for structurally stable G9a proteins that are catalytically incompetent due to aberrant interactions either with histone H3 tail or with S-adenosylmethionine. Heterozygous mice carrying a patient-derived variant exhibit growth retardation, facial/skull dysmorphia and aberrant behavior. Here we report pathogenic EHMT2 variants that likely exert dominant-negative effect on GLP/G9a complexes and thus genocopy the EHMT1 haploinsufficiency via a distinct molecular mechanism, defining an autosomal dominant EHMT2 -related Kleefstra syndrome.
Electrolyte-Regulated Epitaxial-Like Gradient Interface for Stable 4.8 V LiCoO <sub>2</sub>
10 recommendations for strengthening citizen science for improved societal and ecological outcomes: A co-produced analysis of challenges and opportunities in the 21st century
Citizen science plays an increasingly important role in generating scientific knowledge and supporting environmental and social action. However, its potential to address complex global challenges remains underutilised. This study explores how citizen science can be improved by involving the public in all stages of scientific research. Using participatory research methods, online surveys and group discussions were conducted with researchers, citizen scientists, and Indigenous participants. Thematic coding was used to identify key challenges, opportunities, and best practices to enhance citizen science initiatives. Additionally, nine case studies were reported using the Standardised Data on Initiatives (STARDIT) reporting tool. The study identified key strategies for improving involvement, engagement and retention in citizen science initiatives. Findings underscore the importance of inclusive, evidence-informed approaches such as targeted outreach, fair compensation, tailored support, and co-creation practices. Ensuring data quality and fostering trust require adherence to FAIR data principles (findable, accessible, interoperable and reusable), transparent validation and sharing processes, and establishing ethical research partnerships. Persistent challenges include short-term funding, which undermines long-term project sustainability, and the lack of centralised support for ethics and project management. Formal recognition of citizen scientists through co-authorship, standardised training, and professional development opportunities can further strengthen involvement and build capacity. Finally, emerging technologies, including artificial intelligence and open data platforms, present opportunities to scale and improve efficiency, provided they are implemented with appropriate ethical safeguards and investment. Drawing together these insights, we provide 10 actionable recommendations for citizen science in the 21 st century. These highlight the importance of embedding citizen science in national research infrastructure, education, and policy, alongside consistent evaluation and reporting, to improve its inclusivity, longevity, and impact. We conclude by arguing that as the world confronts climate change, public health crises, and biodiversity loss, broader public involvement in science is key for equitable, efficient and evidence-informed responses.
Programmable In Vivo Synthesis of Quantum Dots
ABSTRACT In vivo synthesis of quantum dots (QDs) is fundamentally hindered by the inability to control the spatiotemporal coupling of ionic precursors in living organisms. Herein, we present a s patially h ierarchical i ntegrated n anosynth e sizer (SHINE, FtAg@SS/SiO 2 ‐Se) for the programmable biosynthesis of silver selenide (Ag 2 Se) QDs within tumors. The SHINE integrates a ferritin encapsulating silver source with a custom‐synthesized selenium source, localized on a physically isolated glutathione (GSH)‐responsive silica shell doped with disulfide bonds. Crucially, the thickness of such a shell has provided precise trigger time control over the synthesis. Upon entry into the tumor microenvironment, the elevated GSH triggers a sequential cascade: cleavage of the diselenide bonds generates reactive selenium species, followed by rupture of the silica shell to release the silver‐loaded ferritin, thereby enabling spatially and temporally controlled in situ synthesis of Ag 2 Se QDs. The SHINE has been validated for high‐contrast bioimaging in the second near‐infrared window in live mice. Furthermore, the synthesis process and the resulting QDs orchestrate a synergistic antitumor effect by depleting GSH to enhance oxidative stress and conferring potent photothermal conversion, leading to significant tumor suppression. This work establishes a generalizable strategy for the controlled fabrication of functional nanomaterials in vivo.
Changes in stomatal density and leaf area per mass induced by sunlight acclimation in Bertholletia excelsa and Carapa guianensis
Kinetic model of partial agonism reveals cellular basis of ligand efficacy
A deep learning framework for efficient pathology image analysis
Abstract Artificial intelligence has transformed digital pathology by enabling biomarker prediction from high-resolution whole-slide images. However, current methods are computationally inefficient, processing thousands of redundant tiles per slide and requiring complex aggregation models. We introduce EAGLE (Efficient Approach for Guided Local Examination), a deep learning framework that emulates pathologists by selectively analyzing informative regions. EAGLE combines task-agnostic tile selection with detailed feature extraction and is benchmarked against leading slide- and tile-level foundation models across 43 tasks from nine cancer types spanning morphology, biomarker prediction, treatment response and prognosis. EAGLE outperforms patch aggregation methods by up to 23% and achieves the highest overall classification performance. It processes one slide in 2.27 s, reducing computational time by more than 99% compared with existing models. This efficiency supports rapid and auditable workflows by enabling review of the exact tiles used for each prediction and reducing dependence on high-performance computing. By reliably identifying informative regions and minimizing artifacts, EAGLE provides robust and auditable outputs, supported by systematic negative controls and attention concentration analyses. Its unified embedding enables rapid slide search, integration into multi-omics pipelines and emerging clinical foundation models.
Stereoretentive and Regioselective Late-Stage C–H Glycosylation
Silenced and privileged voices in media discourses: Climate change and social capital
Media representations and narratives around climate change are often dominated by certain voices whilst others are excluded or marginalized. This study investigates media portrayal of climate change around Glasgow’s COP26, focusing on the prominence or exclusion of certain voices. Analyzing US and UK newspaper coverage, it identifies variances in representation, with Indigenous and minority voices marginalized in favor of political, scientific, and activist perspectives from the Global North. Through content analysis, the research explores how power, access, and frames shape media narratives on climate change, underscoring the need for more inclusive discussions.
High Resistivity and Low Defect Covalent Organic Frameworks for Highly Stable and Low Dose X‐Ray Detection
ABSTRACT Direct x‐ray detection technology has long been constrained by trade‐offs between the extracted charge‐carrier signal and mobile‐metal‐ion noise under applied electric fields in conventional semiconductor materials. Here, we report the first demonstration of a low‐defect covalent organic framework (COF)‐based direct X‐ray detector, employing COF366‐M (M = Co, Cu) as the active layer. By incorporating metal ions into a porphyrin‐centered crystalline framework linked through multiple coordinate bonds, COF366‐M enhances x‐ray attenuation while effectively preventing ion migration with negligible current drift of ∼10 −18 A·cm −1 ·V −1 ·s −1 under the operating electric fields. The highly ordered nanochannels in COF366‐M exclude unintended ion doping and exhibit high resistivity along with a low defect level suitable for x‐ray detection. The addition of carbon nanotubes (CNTs) further enhances electron‐hole separation and creates charge‐transport pathways. The device achieves a high sensitivity of up to 11,784 µC·Gy −1 ·cm − 2 , a low detection limit of 39 nGy·s −1 , and excellent operational stability, with no degradation after a high cumulative x‐ray dose of 148 Gy. Moreover, the fully environment‐friendly composition ensures intrinsic environmental friendliness. This work not only validates COFs as a promising platform for high‐performance, stable, and green x‐ray detection, but also provides a molecular‐level paradigm for designing next‐generation low‐dose radiation sensing materials.
Influencing factors and prediction of creativity among college students in traditional Chinese medicine schools: network analysis
Synergistic modulation of cAMP and cGMP rescues hemin-induced plasma membrane fragmentation
Pre-existing antibody and T cell responses to SaCas9, AsCas12a and CasΦ are comparable in naïve individuals
Abstract Cas9 proteins are derived from human pathogens and are immunogenic, thereby raising potential safety concerns and limiting clinical effectiveness when using Cas9 as a gene-editing tool. Cas orthologs developed from organisms not directly associated with human infections may thus be safer. Here we compare the immunogenicity risk of SaCas9 (derived from the human pathogen, Staphylococcus aureus ), AsCas12a (derived from the human commensal, Acidaminococcus sp.) and CasΦ (derived from a bacteria phage, Biggiephage). Ex vivo and in vitro analyses show that SaCas9, AsCas12a and CasΦ are recognized similarly by antibodies and T cells from unimmunized individuals. Using mass-spectrometry to identify MHC-I-bound peptides, we find SaCas9, AsCas12a and CasΦ peptides presented on 9 MHC-I proteins commonly found in the North American population. Our results thus indicate that AsCas12a and CasΦ do not present a less immunogenic alternative to Cas9, and underscore the need for systematic immunogenicity evaluation of all Cas proteins intended for clinical use.
Regio- and Enantioselective Alkoxycarbonylation of Unactivated Terminal Alkenes under Palladium-Bromide-Monophosphine Catalysis
Probability of a timely vocal response in mother-infant interaction and later psychiatric diagnosis: A case-control study
Patterns of parent-child interactions are commonly cited as being predictive of later psychiatric disorders but precisely which elements of these interactions are important is rarely clear, potentially affecting the effective targeting of interventions in young children. The current study aimed to examine the relationship between timely vocal response during parent-child interactions (i.e., the probability of mothers responding to their child within a specified time period and vice versa), and later psychiatric diagnosis. Drawing on data from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort, a case control study was conducted based on infant-mother video observations of children assessed for neuropsychiatric disorders using the parent-reported Development and Wellbeing Assessment (DAWBA) at seven years of age (103 controls and 55 cases). Empirical examination suggested that 1 second represented the optimal threshold for maternal responses and 8 seconds for child responses. Only the maternal measure was found to predict later psychiatric disorders, with evidence of associations limited to hyperactivity and conduct disorders. These associations were not sensitive to either maternal education or child sex. The results are discussed in terms of the value of precise interpretation of early mother/child interaction and for the potential for providing targeted intervention to the population concerned.