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Instant and low-cost detection of urinary microalbumin using smartphone technology and a paper-based platform with a colorimetric ratio analysis
Patterns and drivers of diatom diversity and abundance in the global ocean
Abstract Diatoms constitute one of the most diverse and ecologically important phytoplankton groups, yet their large-scale diversity patterns and drivers of abundance are unclear due to limited observations. Here, we utilize Tara Oceans molecular and morphological data, spanning pole to pole, to describe marine diatom diversity, abundance, and environmental adaptation and acclimation strategies. The dominance of diatoms among phytoplankton in terms of relative abundance and diversity is confirmed, and the most prevalent genera are Chaetoceros , Thalassiosira , Actinocyclus and Pseudo-nitzschia . We define 25 distinct diatom communities with varying environmental preferences illustrative of different life strategies. The Arctic Ocean stands out as a diatom hotspot with 6 of the diatom communities being exclusive to it. Light harvesting and photoprotection are among the cellular functions in which natural diatom populations invest the bulk of their transcriptional efforts. This comprehensive study sheds light on marine diatom distributions, offering insights to assess impacts of global change and oceanic anthropogenic impacts.
Floral reward traits change between sexual phases in two Helleborus species
Cardiovascular post-acute sequelae of SARS-CoV-2 in children and adolescents: cohort study using electronic health records
Identification of M1 macrophage infiltration-related genes for immunotherapy in Her2-positive breast cancer based on bioinformatics analysis and machine learning
An innovative approach using CRISPR-ribonucleoprotein packaged in virus-like particles to generate genetically engineered mouse models
Abstract Genetically engineered mouse models (GEMMs) are crucial for investigating disease mechanisms, developing therapeutic strategies, and advancing fundamental biological research. While CRISPR gene editing has greatly facilitated the creation of these models, existing techniques still present technical challenges and efficiency limitations. Here, we establish a CRISPR-VLP-induced targeted mutagenesis (CRISPR-VIM) strategy, enabling precise genome editing by co-culturing zygotes with virus-like particle (VLP)-delivered gene editing ribonucleoproteins (RNPs) without requiring physical manipulation or causing cellular damage. We generate Plin1- and Tyr-knockout mice through VLP-based SpCas9 or adenine base editor (ABE)/sgRNA RNPs and characterize their phenotype and germline transmission. Additionally, we demonstrate cytosine base editor (CBE)/sgRNA-based C-to-T substitution or SpCas9/sgRNA-based knock-in using VLPs. This method further simplifies and accelerates GEMM generation without specialized techniques or equipment. Consequently, the CRISPR-VIM method can facilitate mouse modeling and be applied in various research fields.
Leveraging explainable AI to predict soil respiration sensitivity and its drivers for climate change mitigation
Dynamic categorization rules alter representations in human visual cortex
Publisher Correction: High risk of political bias in black box emotion inference models
Synthesis of aromatic amides from lignin and its derivatives
KIT-6 supported PhAA-Pd complex as a sustainable nanocatalyst for C–O coupling reactions
Abstract A practical and efficient method for synthesizing C–O cross-coupling has been established using a Pd complex anchored on mesoporous KIT-6. This design showcases exceptional efficiency, recoverability, and thermal stability. The synthesized mesostructure underwent comprehensive characterization through techniques such as FT-IR, SEM, XRD, EDX, BET, ICP, and TGA analyses. This catalyst was then successfully applied in C–O cross-coupling reactions. The approach offers several advantages, including rapid reaction times, high yields, excellent product purity, simplicity, environmental friendliness, and straightforward work-up procedures. Importantly, the durable nanohybrid catalyst exhibited no metal leaching and retained its catalytic performance across multiple cycles of use.
Large-scale multi-omics analyses in Hispanic/Latino populations identify genes for cardiometabolic traits
Fabrication and evaluation of 3D printed PLGA/nHA/GO scaffold for bone tissue engineering
Detection of single-mode thermal microwave photons using an underdamped Josephson junction
Long-term preserved bean seeds exhibit high RNA integrity and high germination potential
Suppression of TGF-β/SMAD signaling by an inner nuclear membrane phosphatase complex
Abstract Cytokines of the TGF-β superfamily control essential cell fate decisions via receptor regulated SMAD (R-SMAD) transcription factors. Ligand-induced R-SMAD phosphorylation in the cytosol triggers their activation and nuclear accumulation. We determine how R-SMADs are inactivated by dephosphorylation in the cell nucleus to counteract signaling by TGF-β superfamily ligands. We show that R-SMAD dephosphorylation is mediated by an inner nuclear membrane associated complex containing the scaffold protein MAN1 and the CTDNEP1-NEP1R1 phosphatase. Structural prediction, domain mapping and mutagenesis reveals that MAN1 binds independently to the CTDNEP1-NEP1R1 phosphatase and R-SMADs to promote their inactivation by dephosphorylation. Disruption of this complex causes nuclear accumulation of R-SMADs and aberrant signaling, even in the absence of TGF-β ligands. These findings establish CTDNEP1-NEP1R1 as the R-SMAD phosphatase, reveal the mechanistic basis for TGF-β signaling inactivation and highlight how this process is disrupted by disease-associated MAN1 mutations.
The Conundrum of Treating de novo metastatic Hormone-Sensitive Prostate Cancer
Tensor-FLAMINGO unravels the complexity of single-cell spatial architectures of genomes at high-resolution
Remotely sensed data contribution in predicting the distribution of native Mediterranean species
Abstract The global change threats significantly alters the ecological distribution of species across different ecosystems. Species distribution models (SDMs) are considered a widely used tool for assessing the global impact on biodiversity. Recently, remote sensing data have been used in a growing number of studies to predict species distribution and improve SDMs performance. This study evaluates the contribution of spectral indices in species distribution modeling using MaxEnt. We compared models based on spectral indices data (RS-only), environmental variables (EN-only), and their combination (CM) to predict the distribution of three key Mediterranean native species: Thymelaea hirsuta, Ononis vaginalis, and Limoniastrum monopetalum. The combined models (CM) demonstrated superior performance with excellent accuracy measures values compared to other models. Jackknife tests revealed both environmental factors (e.g., distance to coastline, mean temperature of wettest and driest quarters) and spectral indices (e.g., NDWI, LST) contributed substantially to predicting the studied species. The findings emphasize the importance of integrating diverse data sources to improve the accuracy of SDMs, particularly in heterogeneous landscapes like the Mediterranean region. This integrated approach provides a more comprehensive understanding of species spreading patterns and is critical for effective management and conservation strategies.