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A data-driven latent variable approach to validating the research domain criteria framework
Spatiotemporal evolution of landscape ecological risk and its driving factors of the Beijing–Tianjin–Hebei major mineral belt, 1985–2022
Incomplete human reference genomes can drive false sex biases and expose patient-identifying information in metagenomic data
Abstract As next-generation sequencing technologies produce deeper genome coverages at lower costs, there is a critical need for reliable computational host DNA removal in metagenomic data. We find that insufficient host filtration using prior human genome references can introduce false sex biases and inadvertently permit flow-through of host-specific DNA during bioinformatic analyses, which could be exploited for individual identification. To address these issues, we introduce and benchmark three host filtration methods of varying throughput, with concomitant applications across low biomass samples such as skin and high microbial biomass datasets including fecal samples. We find that these methods are important for obtaining accurate results in low biomass samples (e.g., tissue, skin). Overall, we demonstrate that rigorous host filtration is a key component of privacy-minded analyses of patient microbiomes and provide computationally efficient pipelines for accomplishing this task on large-scale datasets.
First record of microplastic contamination in adult endemic amazonian anuran species
Abstract The microplastics (MPs), due to their high dispersion and bioaccumulation rates, have been identified in various animal groups, such as anuran amphibians during both larval and adult stages. However, current studies on adult anuran amphibians focus on assessing only one exposure route, the digestive system, while other routes remain underestimated. Therefore, this present study aimed to evaluate the degree of contamination in the digestive, respiratory, and integumentary systems, in situ, of two endemic Amazonian adult anuran species (Physalaemus ephippifer and Boana multifasciata). From this, we identified and characterized microplastic particles for each exposure route, assessed the effects of morphometric measures on the total MP contamination level and in the gastrointestinal tract (GIT). Additionally, we determined different contamination indices and how they vary according to species and systems. Based on our data, the digestive and integumentary exposure routes showed the highest contamination levels for both species. Additionally, variations in MP contamination levels indicated that P. ephippifer had a higher level of MP contamination. Thus, this study provides the first evidence of microplastic exposure through respiratory and integumentary routes in adult anurans in situ, and it is the first to identify MP contamination in terrestrial biomonitors in the Amazon.
Lymphatic platelet thrombosis limits bone repair by precluding lymphatic transporting DAMPs
Advancements in Frank’s sign Identification using deep learning on 3D brain MRI
Incremental accumulation of linguistic context in artificial and biological neural networks
Evaluating the effectiveness of handheld ultrasound in primary blast lung injury: a comprehensive study
Numerous rRNA molecules form the apicomplexan mitoribosome via repurposed protein and RNA elements
Abstract Mitochondrial ribosomes (mitoribosomes) are essential, and their function of synthesising mitochondrial proteins is universal. The core of almost all mitoribosomes is formed from a small number of long and self-folding rRNA molecules. In contrast, the mitoribosome of the apicomplexan parasite Toxoplasma gondii assembles from over 50 extremely short rRNA molecules. Here, we use cryo-EM to discover the features that enable this unusual mitoribosome to perform its function. We reveal that poly-A tails added to rRNA molecules are integrated into the ribosome, and we demonstrate their essentiality for mitoribosome formation and for parasite survival. This is a distinct function for poly-A tails, which are otherwise known primarily as stabilisers of messenger RNAs. Furthermore, while ribosomes typically consist of unique rRNA sequences, here nine sequences are used twice, each copy integrated in a different mitoribosome domain, revealing one of the mechanisms enabling the extreme mitochondrial genome reduction characteristic to Apicomplexa and to a large group of related microbial eukaryotes. Finally, several transcription factor-like proteins are repurposed to compensate for reduced or lost critical ribosomal domains, including members of the ApiAP2 family thus far considered to be DNA-binding transcription factors.
Evaluation of the corrosion resistance of bronze patina or/and protective coating on the surface of the archaeological coins
Abstract Archaeological coins are considered essential sources of historical documentation. Over time, they are subjected to corrosion processes that gradually alter their appearance, shape, and composition. This study aims to evaluate the effects of the patina and/or protective coating on the corrosion process. Protection of the original coin surface was crucial following the completion of the cleaning protocol. Various finishes of coin fragments (uncoated, aged, and freshly coated) were investigated to determine their chemical composition, nature of the patina, and corrosion products on their surface using stereo microscopy(SM), X-ray diffraction (XRD), and scanning electron microscopy (SEM) equipped with energy dispersive X-ray spectroscopy (EDX). The analysis revealed that the coins were composed of a Cu–Sn- and Pb bronze alloy. Furthermore, the efficiency of the patina and/or protective coatings on the coin fragments was evaluated using potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV) techniques. The highest protection was achieved for patinated-freshly protective coated fragments, while the most corrosive fragments were those affected by bronze diseases.
Liquid-infused nanostructured composite as a high-performance thermal interface material for effective cooling
Novel adaptive immune systems in pristine Antarctic soils
Abstract Antarctic environments are dominated by microorganisms, which are vulnerable to viral infection. Although several studies have investigated the phylogenetic repertoire of bacteria and viruses in these poly-extreme environments with freezing temperatures, high ultra violet irradiation levels, low moisture availability and hyper-oligotrophy, the evolutionary mechanisms governing microbial immunity remain poorly understood. Using genome-resolved metagenomics, we test the hypothesis that Antarctic poly-extreme high-latitude microbiomes harbour diverse adaptive immune systems. Our analysis reveals the prevalence of prophages in bacterial genomes (Bacteroidota and Verrucomicrobiota), suggesting the significance of lysogenic infection strategies in Antarctic soils. Furthermore, we demonstrate the presence of diverse CRISPR-Cas arrays, including Class 1 arrays (Types I-B, I-C, and I-E), alongside systems exhibiting novel gene architecture among their effector cas genes. Notably, a Class 2 system featuring type V variants lacks CRISPR arrays, encodes Cas1 and Cas2 adaptation module genes. Phylogenetic analysis of Cas12 effector proteins hints at divergent evolutionary histories compared to classified type V effectors and indicates that TnpB is likely the ancestor of Cas12 nucleases. Our findings suggest substantial novelty in Antarctic cas sequences, likely driven by strong selective pressures. These results underscore the role of viral infection as a key evolutionary driver shaping polar microbiomes.
A metal-trap tests and refines blueprints to engineer cellular protein metalation with different elements
Abstract It has been challenging to test how proteins acquire specific metals in cells. The speciation of metalation is thought to depend on the preferences of proteins for different metals competing at intracellular metal-availabilities. This implies mis-metalation may occur if proteins become mis-matched to metal-availabilities in heterologous cells. Here we use a cyanobacterial Mn II -cupin (MncA) as a metal trap, to test predictions of metalation. By re-folding MncA in buffered competing metals, metal-preferences are determined. Relating metal-preferences to metal-availabilities estimated using cellular metal sensors, predicts mis-metalation of MncA with Fe II in E. coli . After expression in E. coli , predominantly Fe II -bound MncA is isolated experimentally. It is predicted that in metal-supplemented viable cells metal-MncA speciation should switch. Mn II -, Co II -, or Ni II -MncA are recovered from the respective metal-supplemented cells. Differences between observed and predicted metal-MncA speciation are used to refine estimated metal availabilities. Values are provided as blueprints to guide engineering biological protein metalation.
Development and assessment of a mortality risk prediction nomogram model for pneumocystis disease in ICU within 28 days
Enhanced CH4 emissions from global wildfires likely due to undetected small fires
Abstract Monitoring methane (CH4) emissions from terrestrial ecosystems is essential for assessing the relative contributions of natural and anthropogenic factors leading to climate change and shaping global climate goals. Fires are a significant source of atmospheric CH4, with the increasing frequency of megafires amplifying their impact. Global fire emissions exhibit large spatiotemporal variations, making the magnitude and dynamics difficult to characterize accurately. In this study, we reconstruct global fire CH4 emissions by integrating satellite carbon monoxide (CO)-based atmospheric inversion with well-constrained fire CH4 to CO emission ratio maps. Here we show that global fire CH4 emissions averaged 24.0 (17.7–30.4) Tg yr−1 from 2003 to 2020, approximately 27% higher (equivalent to 5.1 Tg yr−1) than average estimates from four widely used fire emission models. This discrepancy likely stems from undetected small fires and underrepresented emission intensities in coarse-resolution data. Our study highlights the value of atmospheric inversion based on fire tracers like CO to track fire-carbon-climate feedback.
Machine learning approach for predicting tramp elements in the basic oxygen furnace based on the compiled steel scrap mix
Abstract In the blast furnace and basic oxygen furnace route, pig iron and steel scrap are used as resources for steel production. The scrap content can consist of many different types of scrap varying in origin and composition. This makes it difficult to compile the scrap mix and predict the future chemical analysis in the converter. When compiling the scrap mix, steel manufacturers often rely on experience and trials. In this paper, we present a machine learning approach based on XGBoost to predict the chemical element content in the converter. Data from around 115000 heats were analyzed and a model was developed to better predict the content of the tramp elements copper, chromium, molybdenum, phosphorus, nickel, tin and sulphur at the end of the basic oxygen furnace process. The study shows that it is possible to predict the chemical element content for tramp elements in the converter based solely on data available in advance and routinely collected without the necessity of additional sensors or analysis of input material. Given the nature of scrap classifications for (external) scrap types, this is non-trivial. Furthermore, an online model was implemented, accessible via a defined synchronous interface, which allows to optimize the use of different scrap types by predicting the chemical content at the end of the basic oxygen furnace process and simulating with new combinations of input material. Not all types of steel scrap are always available. With the model developed, new scrap input constellations can now be created to ensure that the quality of the melt is maintained. However, for very accurate predictions, the data from the upstream processes must be of high quality and quantity. Efficient scrap management, monitoring of the scrap input and confusion checks.
Cross-trait multivariate GWAS confirms health implications of pubertal timing
Abstract Pubertal timing is highly variable and is associated with long-term health outcomes. Phenotypes associated with pubertal timing include age at menarche, age at voice break, age at first facial hair and growth spurt, and pubertal timing seems to have a shared genetic architecture between the sexes. However, puberty phenotypes have primarily been assessed separately, failing to account for shared genetics, which limits the reliability of the purported health implications. Here, we model the common genetic architecture for puberty timing using a multivariate GWAS, with an effective population of 514,750 European participants. We find 266 independent variants in 197 loci, including 18 novel variants. Transcriptomic, proteome imputation and fine-mapping analyses reveal genes causal for pubertal timing, including KDM4C, LEPR, CCNC, ACP1, and PCSK1. Linkage disequilibrium score regression and Mendelian randomisation analysis establish causal associations between earlier puberty and both accelerated ageing and the risk of developing cardiovascular disease and osteoporosis. We find that alanine aminotransferase, glycated haemoglobin, high-density lipoprotein cholesterol and Parabacteroides levels are mediators of these relationships, and establish that controlling oily fish and retinol intake may be beneficial for promoting healthy pubertal development.