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A Data-Driven Approach to Enhance the Prediction of Bacteria–Metabolite Interactions in the Human Gut Microbiome Using Enzyme Encodings and Metabolite Structural Embeddings
Get PDFBackground: The human gut microbiome is critical for host health by facilitating essential metabolic processes. Our study presents a data-driven analysis across 312 bacterial species and 154 unique metabolites to enhance the understanding of underlying metabolic processes in gut bacteria. The focus of the study was to create a strategy to generate a theoretical (negative) set for binary classification models to predict the consumption and production of metabolites in the human gut microbiome. Results: Our models achieved median balanced accuracies of 0.74 for consumption predictions and 0.95 for production predictions, highlighting the effectiveness of this approach in generating reliable negative sets. Additionally, we applied a kernel principal component analysis for dimensionality reduction. The consumption model with a polynomial kernel, and the production model with a radial basis function with 32 reduced features, showed median accuracies of 0.58 and 0.67, respectively. This demonstrates that biological information can still be captured, albeit with some loss, even after reducing the number of features. Furthermore, our models were validated on six previously unseen cases, achieving five correct predictions for consumption and four for production, demonstrating alignment with known biological outcomes. Conclusions: These findings highlight the potential of integrating data-driven approaches with machine learning techniques to enhance our understanding of gut microbiome metabolism. This work provides a foundation for creating bacteria–metabolite datasets to enhance machine learning-based predictive tools, with potential applications in developing therapeutic methods targeting gut microbes
What ‘unexplored’ means: mapping regions with digitized natural history records to look for ‘biodiversity blindspots’
Get PDFWe examined global records of accessible natural history voucher collections (with publicly available data and reliable locality data) for terrestrial and freshwater vascular plants, fungi, freshwater fishes, birds, mammals, and herpetofauna (amphibians and reptiles) and highlight areas of the world that would be considered undersampled and sometimes called ‘unexplored’ (i.e., have relatively low, or no evidence of, past sampling efforts) under typical Western-scientific descriptions. We also question what ‘unexplored’ may mean in these contexts and explain how replacing the term in favor of more nuanced phrasing (e.g., ‘biodiversity blindspots,’ which emphasizes the lack of publicly available data about specimens) can mitigate future misunderstandings of natural history science. We also highlight geographic regions where there are relatively few or no publicly available natural history records to raise awareness about habitats that might be worthy of future natural history research and conservation. A major finding is that many of the areas that appear ‘unexplored’ may be in countries whose collections are not digitized (i.e., they don’t have metadata such as GPS coordinates about their voucher specimens publicly available). We call for museums to prioritize digitizing those collections from these ‘biodiversity blindspots’ and for increased funding for museums to aid in these efforts. We also argue for increased scientific infrastructure so that more reference collections with vouchers can be kept in the countries of origin (particularly those countries lacking such infrastructure currently)
With Vim and Courage: Confederate Soldiers and the Politics of War
No full textThe Confederate cause has captivated historians for many decades. At first glance, the Confederacy embodies a persistent effort to promote white supremacy, the planter class, and independence. While this assessment is accurate, individual Confederate soldiers possess diverse narratives that both challenge and support the labels assigned over the years. The political dimension of the Civil War opens new avenues for scholarly exploration concerning Confederate soldiers. But what insights might this offer regarding the nature of the Confederacy, civilian political engagement, and democracy? The answer to this question is complex and nonlinear. Previous research has acknowledged the numerous reasons why Confederate soldiers enlisted, the factors behind their cause\u27s failure, and why many endured four years of conflict. However, limited attention has been paid to how and whether Confederate soldiers engaged with political affairs. Although studies have examined the political involvement of Union soldiers, this raises the question: What perspectives did Confederates hold regarding their national politics? How did they perceive democracy within the Confederacy? This analysis indicates that Confederate soldiers expressed their ideological views of democracy in practice, reflecting a form of lower “d” democratic participation. While scholars have expanded their understanding of hierarchy and democracy within the Antebellum South, little focus has been directed toward Confederate soldiers’ perceptions of democracy and their engagement with everyday political issues. Confederates responded to military service through various means, developing complex political ideologies along the way. Their engagement with politics reveals their understanding of democracy\u27s role in the South. Consequently, many soldiers cultivated heightened political consciousness and gained a deeper understanding of the war. Their political interactions suggest that many Confederates believed their democratic voices were meaningful within the broader political landscape of the South
The roles of isolation and interspecific interaction in generating the functional diversity of an insular mammal radiation
No full textCommunities that occupy similar environments but vary in the richness of closely related species can illuminate how functional variation and species richness interact to fill ecological space in the absence of abiotic filtering, though this has yet to be explored on an oceanic island where the processes of community assembly may differ from continental settings. In discrete montane communities on the island of Sulawesi, local murine rodent (rats and mice) richness ranges from 7 to 23 species. We measured 17 morphological, ecological, and isotopic traits – both individually and as five multivariate traits – in 40 species to test for the expansion or packing of functional space among nine murine communities. We employed a novel probabilistic approach for integrating intraspecific and community-level trait variance into functional richness. Trait-specific and phylogenetic diversity patterns indicate dynamic community assembly due to variable niche expansion and packing on multiple niche axes. Locomotion and covarying traits such as tail length emerged as a fundamental axis of ecological variation, expanding functional space and enabling the niche packing of other traits such as diet and body size. Though trait divergence often explains functional diversity in island communities, we found that phylogenetic diversity facilitates functional space expansion in some conserved traits such as cranial shape, while more labile traits are overdispersed both within and between island clades, suggesting a role of niche complementarity. Our results evoke interspecific interactions, differences in trait lability, and the independent evolutionary trajectories of each of Sulawesi\u27s six murine clades as central to generating the exceptional functional diversity and species richness in this exceptional, insular radiation
Activity of the mammalian DNA transposon piggyBat from Myotis lucifugus is restricted by its own transposon ends
Get PDFMembers of the piggyBac superfamily of DNA transposons are widely distributed in host genomes ranging from insects to mammals. The human genome has retained five piggyBac-derived genes as domesticated elements although they are no longer mobile. Here, we have investigated the transposition properties of piggyBat from Myotis lucifugus, the only known active mammalian DNA transposon, and show that its low activity in human cells is due to subterminal inhibitory DNA sequences. Activity can be dramatically improved by their removal, suggesting the existence of a mechanism for the suppression of transposon activity. The cryo-electron microscopy structure of the piggyBat transposase pre-synaptic complex showed an unexpected mode of DNA binding and recognition using C-terminal domains that are topologically different from those of the piggyBac transposase. Here we show that structure-based rational re-engineering of the transposase through the removal of putative phosphorylation sites and a changed domain organization - in combination with truncated transposon ends - results in a transposition system that is at least 100-fold more active than wild-type piggyBat
Decoding dynamic landslide hazard processes for a massive refugee camp in Bangladesh
No full textLandslides disrupt human ecology worldwide, making practical hazard assessments essential for saving lives and assets. Dynamic assessments, which capture temporal changes in susceptibility, remain rare due to limited multi-temporal landslide inventories. This study addresses this gap by implementing a slope unit (SU)-based dynamic landslide hazard assessment for the Kutupalong Rohingya Refugee Camp (KTP), a region undergoing rapid environmental and landscape changes due to a massive human influx. Here, we decode dynamic landslide hazard processes by employing a Generalized Additive Model (GAM), a flexible statistical method, to explore how landslides (dependent variables) are linked to independent variables like continuous factors (e.g., slope, soil depth, rainfall) and categorical factors (e.g., soil type, landcover change category). We produced multi-temporal inventories to represent conditions before (2018 and prior) and after (2021 and prior) the establishment of refugee settlements. Anthropogenic modifications, such as distance from roads, land-use/NDVI changes, and rainfall, are treated as dynamic factors, while other factors are considered static predisposing conditions. Our GAM approach performs better than standard machine learning (ML) techniques (e.g., Random Forest, Support Vector Machine, Neural Networks), achieving an overall ROC-AUC of 0.84 and a mean cross-validated AUC of 0.81, compared to AUC (0.64-0.74) for ML models. We also performed uncertainty quantification and repeated random simulations (Monte Carlo simulations) to identify slope units with increased, decreased, or unchanged susceptibility. Priority SUs requiring immediate risk reduction measures are flagged, offering actionable insights for local authorities. Our research findings advance landslide hazard assessments by integrating time-varying dynamic processes with a slope units-based approach and facilitating risk mitigation at KTP
Feral Hog Toxicant
Get PDFA composition and method for killing feral hogs: a bait that is attractive to hogs is mixed with a lethal amount of sodium nitrite, along with sufficient base to inhibit decomposition of the sodium nitrite. At sufficiently high pH, encapsulation of the sodium nitrite is not required to inhibit decomposition. In the absence of substantial decomposition, the sodium nitrite itself is not aversive to the pigs, and may even enhance acceptance of the baits by the pigs. Optionally, an anti-emetic compound is added to the mixture to reduce the likelihood the bait will be vomited. Optionally, an additional toxicant such as luteolin is added to the mixture
A Galerkin Approach to the Generalized Karush-Kuhn-Tucker Conditions for the Solution of an Elliptic Distributed Optimal Control Problem with Pointwise State and Control Constraints
No full textWe develop a convergence analysis for the simplest finite element method for a model linear-quadratic elliptic distributed optimal control problem with pointwise control and state constraints under minimal assumptions on the constraint functions. We then derive the generalized Karush-Kuhn-Tucker conditions for the solution of the optimal control problem from the convergence results of the finite element method and the Karush-Kuhn-Tucker conditions for the solutions of the discrete problems
Refining a chain theorem from matroids to internally 4-connected graphs
Get PDFGraph theory and matroid theory are interconnected with matroids providing a way to generalize and analyze the structural and independence properties within graphs. Chain theorems, vital tools in both matroid and graph theory, enable the analysis of matroid structures associated with graphs. In a significant contribution, Chun, Mayhew, and Oxley [2] established a chain theorem for internally 4-connected binary matroids, clarifying the operations involved. Our research builds upon this by specifying the matroid result to internally 4-connected graphs. The primary goal of our research is to refine this chain theorem for matroids into a chain theorem for internally 4-connected graphs, making it more accessible to individuals less acquainted with matroid theory
Absorbing Markov chain model of PrEP drug adherence to estimate adherence decay rate and probability distribution in clinical trials
No full textPre-exposure prophylaxis (PrEP) is increasingly used to prevent the transmission of H.I.V. in at-risk populations. However, PrEP users may discontinue use of the medicine due to side effects, lower perceived risk, or other reasons. The usage metrics of 594 individuals was tracked over 350 days using the Wisepill electronic monitoring system. We model the PrEP drug adherence level using an absorbing Markov chain with a unique absorbing state. The transition matrix T obtained from the Wisepill data will have a trivial eigenvector (eigendistribution) associated with the first (i.e., largest) eigenvalue 1. The 2nd eigenvalue(s) then become important in determining the asymptotic behavior of the Markov chain, dictating how fast the Markov chain decays to the absorbing state. Under a fairly general assumption, we prove that the second positive eigenvalue is unique and the corresponding eigenvector will have nonnegative entries with exceptions at absorbing states. In addition, we define the asymptotic half life of the absorbing Markov chain directly from the 2nd eigenvalue. We then determine the 2nd eigenvalue of T and the asymptotic half life of the Markov chain, which turns out to be very close to the real half life of the Markov chain. Finally, we interpret the 2nd eigenvector as the relative probability distribution of X∞ with respect to the decay rate of the 2nd eigenvalue. By applying these methods to the Wisepill data, we estimate the half-life of population adherence to be 46 weeks. The bi-weekly decay rate observed in these data from 90 to 100 % adherence is 3 %. This work produces an estimate at which adherence falls over time, given no external intervention is applied. These results suggest an eigenvector-based approach to estimate adherence trends, as well as the timing of interventions to improve adherence