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WNT11 Promotes immune evasion and resistance to Anti-PD-1 therapy in liver metastasis
Customer segmentation in the digital marketing using a Q-learning based differential evolution algorithm integrated with K-means clustering
Effective and well-structured customer segmentation enables organizations to accurately identify and comprehend the distinct characteristics and needs of various customer groups, thereby facilitating the development of more targeted marketing strategies. Contemporary artificial intelligence technologies have emerged as the predominant tools for customer segmentation, owing to their robust capabilities in analyzing complex datasets and extracting profound customer insights. This paper proposes a customer segmentation framework within the realm of digital marketing, which integrates a reinforcement learning-based differential evolution algorithm with K-means clustering using dimensionality reduction techniques to address challenges in the customer segmentation process. Initially, a correlation matrix is used to identify redundant noise and multicollinear features within customer feature groups, and Principal Component Analysis is applied for denoising and dimensionality reduction to enhance the ability of the model to identify potential features. Subsequently, a parameter adaptive adjustment method based on Q-learning is proposed, which significantly augments the clustering performance of K-means. Ultimately, the effectiveness of the proposed method is validated using a Kaggle dataset, and the elbow method is employed to ascertain the optimal number of clusters. Based on the cluster category centers, the typical characteristics of different customer types are analyzed. Furthermore, four widely recognized machine learning methods are employed to classify the clustering results, achieving over 95% classification accuracy on the test set. The experimental results demonstrate that the proposed model exhibits a high degree of customer characteristic identification and segmentation, which not only enhances marketing efficiency and customer satisfaction but also fosters corporate profit growth through the strategic formulation of various marketing initiatives.
Clinical efficacy and safety study of vNOTES for benign ovarian tumors in obese patients
Orbital-order as the driving mechanism for superconductivity in ruthenates
The association between maternal tobacco smoking during pregnancy and the risk of attention-deficit/hyperactivity disorder (ADHD) in offspring: A systematic review and meta-analysis
Introduction Maternal tobacco smoking during pregnancy is a significant public health concern with potential long-lasting effects on child development. ADHD, a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity, may be influenced by prenatal nicotine exposure. This systematic review and meta-analysis examine the association between maternal tobacco smoking during pregnancy and the risk of ADHD in offspring. Methods Following PRISMA guidelines, we searched databases including PubMed, Web of Science, Cochrane Central, Embase, Scopus, CINAHL, LILACS, SciELO, Allied and Complementary Medicine Database (AMED), ERIC, CNKI, HTA Database, Dialnet, EBSCO, LENS, and Google Scholar for studies up to November 1, 2024. We included peer-reviewed studies reporting quantitative effect size estimates for the association between maternal tobacco smoking and ADHD. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). Results We identified 2,981 articles and included 55 studies (4,016,522 participants) in the analysis. The meta-analysis showed a significant association between maternal tobacco smoking during pregnancy and increased risk of ADHD in offspring (pooled Odds Ratio (OR) = 1.71, 95% CI: 1.55-1.88; P < 0.001). Egger’s test indicated no publication bias (p = 0.204), but Begg’s test did (p = 0.042). By employing the trim and fill method, the revised OR was estimated to be 1.54 (95% CI: 1.40–1.70; P < 0.001). The OR were 2.37 (95% CI: 1.72–3.28; P < 0.001) in cross-sectional studies, 1.72 (95% CI: 1.49–2.00; P < 0.001) in case-control studies, and 1.53 (95% CI: 1.34–1.74; P < 0.001) in cohort studies. Meta-regression showed study design and study region significantly influenced heterogeneity (P < 0.10). Sensitivity and subgroup analyses confirmed the robustness of these findings. Conclusion This systematic review and meta-analysis demonstrate a significant association between maternal tobacco smoking during pregnancy and increased odds of ADHD in offspring. These findings highlight the need for prenatal care guidelines and tobacco smoking cessation programs for pregnant women to reduce ADHD risk and promote optimal neurodevelopmental outcomes. Future research should explore underlying mechanisms and potential confounders further.
Unilocular adipocyte and lipid tracer for immunofluorescent images
How energy determines spatial localisation and copy number of molecules in neurons
Abstract In neurons, the quantities of mRNAs and proteins are traditionally assumed to be determined by functional, electrical or genetic factors. Yet, there may also be global, currently unknown computational rules that are valid across different molecular species inside a cell. Surprisingly, our results show that the energy for molecular turnover is a significant cellular expense, en par with spiking cost, and which requires energy-saving strategies. We show that the drive to save energy determines transcript quantities and their location while acting differently on each molecular species depending on the length, longevity and other features of the respective molecule. We combined our own data and experimental reports from five other large-scale mRNA and proteomics screens, comprising more than ten thousand molecular species to reveal the underlying computational principles of molecular localisation. We found that energy minimisation principles explain experimentally-reported exponential rank distributions of mRNA and protein copy numbers. Our results further reveal robust energy benefits when certain mRNA classes are moved into dendrites, for example mRNAs of proteins with long amino acid chains or mRNAs with large non-coding regions and long half-lives proving surprising insights at the level of molecular populations.
A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification
Three-dimensional mapping of the altermagnetic spin splitting in CrSb
Abstract Altermagnetism, a kind of collinear magnetism that is characterized by a momentum-dependent band and spin splitting without net magnetization, has recently attracted considerable interest. Finding altermagnetic materials with large splitting near the Fermi level necessarily requires three-dimensional k-space mapping. While this is crucial for spintronic applications and emergent phenomena, it remains challenging. Here, using synchrotron-based angle-resolved photoemission spectroscopy (ARPES), spin-resolved ARPES and model calculations, we uncover a large altermagnetic splitting, up to ~1.0 eV, near the Fermi level in CrSb. We verify its bulk-type g-wave altermagnetism through systematic three-dimensional k-space mapping, which unambiguously reveals the altermagnetic symmetry and associated nodal planes. Spin-resolved ARPES measurements further verify the spin polarizations of the split bands near Fermi level. Tight-binding model analysis indicates that the large altermagnetic splitting arises from strong third-nearest-neighbor hopping mediated by Sb ions. The large band/spin splitting near Fermi level in metallic CrSb, together with its high T N (up to 705 K) and simple spin configuration, paves the way for exploring emergent phenomena and spintronic applications based on altermagnets.
Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses
Attosecond metrology of vacuum-ultraviolet high-order harmonics generated in semiconductors via laser-dressed photoionization of alkali metals
Base editing HbS to HbG-Makassar improves hemoglobin function supporting its use in sickle cell disease
Nanobody-thioesterase chimeras to specifically target protein palmitoylation
Abstract The complexity of the cellular proteome is massively expanded by a repertoire of chemically distinct reversible post-translational modifications (PTMs) that control protein localisation, interactions, and function. The temporal and spatial control of these PTMs is central to organism physiology, and mis-regulation of PTMs is a hallmark of many diseases. Here we present an approach to manipulate PTMs on target proteins using nanobodies fused to enzymes that control these PTMs. Anti-GFP nanobodies fused to thioesterases (which depalmitoylate protein cysteines) depalmitoylate GFP tagged substrates. A chemogenetic approach to enhance nanobody affinity for its target enables temporal control of target depalmitoylation. Using a thioesterase fused to a nanobody directed against the Ca(v)1.2 beta subunit we reduce palmitoylation of the Ca(v)1.2 alpha subunit, modifying the channel’s voltage dependence and arrhythmia susceptibility in stem cell derived cardiac myocytes. We conclude that nanobody enzyme chimeras represent an approach to specifically manipulate PTMs, with applications in both the laboratory and the clinic.
Flavones enrich rhizosphere Pseudomonas to enhance nitrogen utilization and secondary root growth in Populus
Abstract Plant growth behavior is a function of genetic network architecture. The importance of root microbiome variation driving plant functional traits is increasingly recognized, but the genetic mechanisms governing this variation are less studied. Here, we collect roots and rhizosphere soils from nine Populus species belonging to four sections ( Leuce , Aigeiros , Tacamahaca , and Turanga ), generate metabolite and transcription data for roots and microbiota data for rhizospheres, and conduct comprehensive multi-omics analyses. We demonstrate that the roots of vigorous Leuce poplar enrich more Pseudomonas , compared with the poorly performing poplar. Moreover, we confirm that Pseudomonas is strongly associated with tricin and apigenin biosynthesis and identify that gene GLABRA3 ( GL3 ) is critical for tricin secretion. The elevated tricin secretion via constitutive transcription of PopGL3 and Chalcone synthase ( PopCHS4 ) can drive Pseudomonas colonization in the rhizosphere and further enhance poplar growth, nitrogen acquisition, and secondary root development in nitrogen-poor soil. This study reveals that plant-metabolite-microbe regulation patterns contribute to the poplar fitness and thoroughly decodes the key regulatory mechanisms of tricin, and provides insights into the interactions of the plant’s key metabolites with its transcriptome and rhizosphere microbes.
Metabolic deficiencies underlie reduced plasmacytoid dendritic cell IFN-I production following viral infection
Abstract Type I Interferons (IFN-I) are central to host protection against viral infections, with plasmacytoid dendritic cells (pDC) being the most significant source, yet pDCs lose their IFN-I production capacity following an initial burst of IFN-I, resulting in susceptibility to secondary infections. The underlying mechanisms of these dynamics are not well understood. Here we find that viral infection reduces the capacity of pDCs to engage both oxidative and glycolytic metabolism. Mechanistically, we identify lactate dehydrogenase B (LDHB) as a positive regulator of pDC IFN-I production in mice and humans; meanwhile, LDHB deficiency is associated with suppressed IFN-I production, pDC metabolic capacity, and viral control following infection. In addition, preservation of LDHB expression is sufficient to partially retain the function of otherwise exhausted pDCs, both in vitro and in vivo. Furthermore, restoring LDHB in vivo in pDCs from infected mice increases IFNAR-dependent, infection-associated pathology. Our work thus identifies a mechanism for balancing immunity and pathology during viral infections, while also providing insight into the highly preserved infection-driven pDC inhibition.
Author Correction: Integrating social vulnerability into high-resolution global flood risk mapping
Structural basis of inhibition of human NaV1.8 by the tarantula venom peptide Protoxin-I
Abstract Voltage-gated sodium channels (Na V s) selectively permit diffusion of sodium ions across the cell membrane and, in excitable cells, are responsible for propagating action potentials. One of the nine human Na V isoforms, Na V 1.8, is a promising target for analgesics, and selective inhibitors are of interest as therapeutics. One such inhibitor, the gating-modifier peptide Protoxin-I derived from tarantula venom, blocks channel opening by shifting the activation voltage threshold to more depolarized potentials, but the structural basis for this inhibition has not previously been determined. Using monolayer graphene grids, we report the cryogenic electron microscopy structures of full-length human apo-Na V 1.8 and the Protoxin-I-bound complex at 3.1 Å and 2.8 Å resolution, respectively. The apo structure shows an unexpected movement of the Domain I S4-S5 helix, and VSD I was unresolvable. We find that Protoxin-I binds to and displaces the VSD II S3-S4 linker, hindering translocation of the S4 II helix during activation.
Molecular self-assembly strategy tuning a dry crosslinking protein patch for biocompatible and biodegradable haemostatic sealing
Abstract Uncontrolled haemorrhage is a leading cause of trauma-related fatalities, highlighting the critical need for rapid and effective haemostasis. Current haemostatic materials encounter limitations such as slow clotting and weak mechanical strength, while most of bioadhesives compromise their adhesion performance to wet tissues for biocompatibility and degradability. In this study, a molecular self-assembly strategy is proposed, developing a biocompatible and biodegradable protein-based patch with excellent adhesion performance. This strategy utilizes fibrinogen modified with hydrophobic groups to induce self-assembly into a hydrogel, which is converted into a dry patch. The protein patch enhances adhesion performance on the wet tissue through a dry cross-linking method and robust intra/inter-molecular interactions. This patch demonstrates excellent haemostatic efficacy in both porcine oozing wound and porcine severe acute haemorrhage. It maintains biological functionality, and ensures sustained wound sealing while gradually degrading in vivo, making it a promising candidate for clinical tissue sealing applications.