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Genetic exchange networks bridge mobile DNA vehicles in the bacterial pathogen Listeria monocytogenes
Effective in vivo RNA base editing via engineered cytidine deaminase APOBECs fused with PUF proteins
Exploring the contribution of risk factors on major illness: a microsimulation study in England, 2023-2043
Abstract Multimorbidity is projected to continue increasing in England and many other countries. Here, we use a validated microsimulation model to quantify the potential impact of improving exposure levels of eight risk factors on the burden of major illness among adults aged 30+ in England between 2023-2043. We find that the biggest contributors to incident major illness are body mass index, smoking, systolic blood pressure, and physical inactivity. Theoretical minimum risk exposure levels of all risk factors could reduce 2043 major illness prevalence by 2 percentage points (95% uncertainty intervals: 1.3, 2.7) compared to the continuing trends (base-case) scenario; under a 10% improvement in all risk factors, we project a 0.3 percentage points (0.2, 0.4) reduction in major illness. The impact on health inequalities is mixed. Our findings show that large improvements in risk factors are unlikely to substantially reduce the major illness burden by 2043 due to population ageing.
Decadal changes in wind speed have offset and then aggravated the impact of warming on maize production in China since 1980
Phage diversity mirrors bacterial strain diversity in the honey bee gut microbiota
Abstract Bacteriophages (phages) play a crucial role in shaping bacterial communities. Documenting the relationship between phage and bacterial diversity in natural systems is fundamental to understand eco-evolutionary dynamics that shape community composition, such as host specificity, emergence of phage resistance and phage-driven microbial diversification. However, our current understanding of this relationship is still limited, particularly in animal-associated microbiomes. Here, we analyze paired bacterial and viral metagenomics data from the gut microbiota of 49 individual honeybees and reconstruct the phage-bacteria interaction network by leveraging CRISPR spacer matches and genome homology. The resulting interaction network displays a highly modular structure with nested phage-bacteria interactions within each module. Viral and bacterial alpha and beta diversity are correlated, particularly at the bacterial strain level and when considering the interaction network. Overall, our results suggest that the most relevant approach to study phage-bacteria diversity patterns should rely on strain-level resolution and the explicit use of the interaction network. This may explain why previous studies have obtained mixed results when testing for phage-bacteria diversity correlations. Finally, we call for further studies building up on these correlation patterns to probe the underlying mechanisms by considering both bottom-up and top-down regulatory mechanisms in microbiome assembly.
Pmt4 recognizes two separate acceptor sites to O-mannosylate in the S/T-rich regions of substrate proteins
Maintaining sulfur supply to the symbiosome delays nodule senescence in soybean
Regenerating liver uses ammonia to support de novo pyrimidine synthesis and cell proliferation
Low-strain metal–organic framework negative electrode for stable all-solid-state batteries
Heterologous sequential immunization using chimeric mRNA and protein vaccines with HA-stem and S-RBD enhanced protective mucosal immunity against influenza and COVID-19
Revealing interfacial failure mechanism of silicon based all solid state batteries via cryogenic electron microscopy
Evolutionary bi-level neural architecture search with training: A framework for color classification
Abstract The design of Artificial Neural Networks (ANNs) for classification tasks has been a topic of interest. However, defining an optimal ANN architecture remains challenging, especially when considering resource constraints and the large number of design parameters. This paper proposes an Evolutionary Bi-Level Neural Architecture Search with Training (EB-LNAST) approach that simultaneously optimizes the architecture, weights, and biases of a neural network using a bi-level optimization strategy. The upper level focuses on minimizing the network complexity penalized by the lower level performance function, while the lower level optimizes training parameters to minimize the loss function and maximize the predictive performance. The proposal is evaluated on a real-world color classification task and the WDBC dataset, demonstrating statistically significant improvements over traditional machine learning algorithms, as well as advanced models. Compared to Multilayer Perceptron (MLP) based algorithms, EB-LNAST achieves superior predictive performance when the architecture is fixed, and remains competitive, with a marginal reduction in performance of no more than $$0.99\%$$ , even when compared against MLPs optimized with extensive hyperparameter tuning, including architecture, activation functions, regularization, and optimizers. Remarkably, EB-LNAST achieves up to a $$99.66\%$$ reduction in model size, highlighting its ability to discover compact and efficient architectures. EB-LNAST is a reliable alternative for generating compact and effective neural network architectures in accordance with the problem’s requirements, enabling efficient exploration of the search space while maintaining or exceeding the predictive performance of state-of-the-art classification algorithms.
HER2DX in older patients with HER2-positive early breast cancer: extended follow-up from the RESPECT trial of trastuzumab ± chemotherapy
Abstract Older adults with HER2-positive early breast cancer are underrepresented in clinical trials, and the benefit of chemotherapy in this population remains uncertain. We evaluated the HER2DX genomic assay within the randomized RESPECT trial (NCT01104935), which compared adjuvant trastuzumab with or without chemotherapy in patients aged 70–80 years. In this prespecified translational analysis (Trans-RESPECT), HER2DX scores were available for 154 patients. The HER2DX risk score classified 74.0% as low risk and 26.0% as high risk. Ten-year relapse-free and overall survival were higher in the low-risk group. HER2DX remained independently associated with overall survival in multivariable analysis. The HER2DX immune, luminal, and proliferation signatures that compose the risk score were also prognostic. While the HER2DX pCR score was not prognostic overall, exploratory subgroup analyses suggested a potential survival benefit from chemotherapy in the pCR-high group. HER2DX offers prognostic value and may guide chemotherapy use in older patients with HER2-positive early breast cancer. Clinical Trial Information NCT01104935
Unsteady two dimensional flow of non-newtönian fractional Casson fluid for an edge with heated boundaries
Non-corrosive asymmetric fluorinated aryl sulfonimide lithium salt for high-temperature and high-voltage lithium metal batteries
Interpretable radiomics-based machine learning model for differentiating glioblastoma from primary central nervous system lymphoma using contrast-enhanced T1-weighted imaging
The Genetic Architecture of the Human Corpus Callosum and its Subregions
Abstract The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses and performing associative or executive functions. Identifying which genetic variants underpin CC morphometry can provide molecular insights into the CC’s role in mediating cognitive processes. We developed and used an artificial intelligence based tool to extract the midsagittal CC’s total and regional area and thickness in two large public datasets. We performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685) with generalization to the non-European participants (combined N = 7040). Post-GWAS analyses implicated prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Genetic overlap, and causal genetic liability, between the CC, cerebral cortex features, and neuropsychiatric disorders such as attention-deficit/hyperactivity, bipolar disorders, and Parkinson’s disease were identified.