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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Human health benefits of very-long-chain polyunsaturated fatty acids from microalgae

Microalgae are single-cell, photosynthetic organisms whose biodiversity places them at the forefront of biological producers of high-value molecules including lipids and pigments. Some of these organisms particular are capable of synthesizing n-3 very long chain polyunsaturated fatty acids (VLC-PUFAs), known to have beneficial effects on human health. Indeed, VLC-PUFAs are the precursors of many signaling molecules in humans involved in the complexities of inflammatory processes. Herein, this mini-review provides an inventory of knowledge on the synthesis of VLC-PUFAs in microalgae and on the diversity of signaling molecules (prostanoids, leukotrienes, SPMs, EFOX, isoprostanoids) that arise in humans from VLC-PUFAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Studies of selenium and arsenic mutual protection in human HepG2 cells

Hundreds of millions of people worldwide are exposed to unacceptable levels of carcinogenic inorganic arsenic. Animal models have shown that selenium and arsenic are mutually protective through the formation and elimination of the seleno-bis(S-glutathionyl) arsinium ion [(GS) 2 AsSe] - . Consistent with this, human selenium deficiency in arsenic-endemic regions is associated with arsenic-induced disease, leading to the initiation of human selenium supplementation trials. In contrast to the protective effect observed in vivo, in vitro studies have suggested that selenite increases arsenite cellular retention and toxicity. This difference might be explained by the rapid conversion of selenite to selenide in vivo. In the current study, selenite did not protect the human hepatoma (HepG2) cell line against the toxicity of arsenite at equimolar concentrations, however selenide increased the IC 50 by 2.3-fold. Cytotoxicity assays of arsenite + selenite and arsenite + selenide at different molar ratios revealed higher overall mutual antagonism of arsenite + selenide toxicity than arsenite + selenite. Despite this protective effect, in comparison to 75 Se-selenite, HepG2 cells in suspension were at least 3-fold more efficient at accumulating selenium from reduced 75 Se-selenide, and its accumulation was further increased by arsenite. X-ray fluorescence imaging of HepG2 cells also showed that arsenic accumulation, in the presence of selenide, was higher than in the presence of selenite. These results are consistent with a greater intracellular availability of selenide relative to selenite for protection against arsenite, and the formation and retention of a less toxic product, possibly [(GS) 2 AsSe] - .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Combination of Human Broadly Neutralizing Antibodies against Hepatitis B Virus HBsAg with Distinct Epitopes Suppresses Escape Mutations

Although there is no effective cure for chronic hepatitis B virus (HBV) infection, antibodies are protective and correlate with recovery from infection. To examine the human antibody response to HBV, we screened 124 vaccinated and 20 infected, spontaneously recovered individuals. The selected individuals produced shared clones of broadly neutralizing antibodies (bNAbs) that targeted 3 non-overlapping epitopes on the HBV S antigen (HBsAg). Single bNAbs protected humanized mice against infection but selected for resistance mutations in mice with prior established infection. In contrast, infection was controlled by a combination of bNAbs targeting non-overlapping epitopes with complementary sensitivity to mutations that commonly emerge during human infection. The co-crystal structure of one of the bNAbs with an HBsAg peptide epitope revealed a stabilized hairpin loop. This structure, which contains residues frequently mutated in clinical immune escape variants, provides a molecular explanation for why immunotherapy for HBV infection may require combinations of complementary bNAbs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Analysis of ionizing radiation induced DNA damage response in human adult stem cells and differentiated neurons

Findings of neurodegenerative features associated with human radiosensitive syndromes such as Ataxia telangiectasia suggest that DNA repair efficiency is crucial for maintaining the functional integrity of central nervous system. To gain a better understanding of ionizing radiation (IR) induced DNA damage response in undifferentiated and differentiated neural cell types and to evaluate the role of ATM in DNA double strand break (DSB) repair, an in vitro human neural cell differentiation model system was utilized in this study. As compared to adult stem cells, differentiated neurons displayed an attenuated DSB repair response (as judged by the persistence of 53BP1 foci) after IR exposure and the attenuation was even more pronounced in stem cells and neurons after suppression of ATM (Ataxia Telangiectasia Mutated) gene product suggesting the importance of ATM for an optimal DSB repair efficiency in human neural cell types. In corroboration with an attenuated DNA damage response, a sharp decline in the expression levels of several DSB repair genes was observed in neurons. Furthermore, our results suggest that cellular differentiation modulates the expression of several genes thereby compromising the DSB repair fidelity in post mitotic neurons. Further studies are required to verify whether or not ATM mediated exacerbation of DNA repair deficiency in differentiated neurons leads to neurodegeneration.

53 binding protein 1↗
DOE OSTI2023

Benzo[$\mathcal{a}$]pyrene toxicokinetics in humans following dietary supplementation with 3,3'-diindolylmethane (DIM) or Brussels sprouts

Utilizing the atto-zeptomole sensitivity of UPLC-accelerator mass spectrometry (UPLC-AMS), we previously demonstrated significant first-pass metabolism following escalating (25–250 ng) oral micro-dosing in humans of [ 14 C]-benzo[a]pyrene ([ 14 C]-BaP). The present study examines the potential for supplementation with Brussels sprouts (BS) or 3,3' -diindolylmethane (DIM) to alter plasma levels of [ 14 C]-BaP and metabolites over a 48-h period following micro-dosing with 50 ng (5.4 nCi) [ 14 C]-BaP. Volunteers were dosed with [ 14 C]-BaP following fourteen days on a cruciferous vegetable restricted diet, or the same diet supplemented for seven days with 50 g of BS or 300 mg of BR-DIM ® prior to dosing. BS or DIM reduced total [ 14 C] recovered from plasma by 56–67% relative to nonintervention. Dietary supplementation with DIM markedly increased T max and reduced C max for [ 14 C]-BaP indicative of slower absorption. Further, both dietary treatments significantly reduced C max values of four downstream BaP metabolites, consistent with delaying BaP absorption. Dietary treatments also appeared to reduce the T 1/2 and the plasma AUC( 0,$\infty$ ) for Unknown Metabolite C, indicating some effect in accelerating clearance of this metabolite. Toxicokinetic constants for other metabolites followed the pattern for [ 14 C]-BaP (metabolite profiles remained relatively consistent) and non-compartmental analysis did not indicate other significant alterations. Significant amounts of metabolites in plasma were at the bay region of [ 14 C]-BaP irrespective of treatment. Although the number of subjects and large interindividual variation are limitations of this study, it represents the first human trial showing dietary intervention altering toxicokinetics of a defined dose of a known human carcinogen.

3,3'-diindolylmethane↗
DOE OSTI2025

Building a predictive model for polycyclic aromatic hydrocarbon dosimetry in organotypically cultured human bronchial epithelial cells using benzo[ a ]pyrene

The airway epithelium is a primary route of exposure for inhaled toxicants, and organotypic culture models represent an important advancement for toxicity testing compared to simple in vitro models that may lack metabolic capability and multicellular structure/communication associated with the bronchial epithelium in vivo. A quantitative understanding of chemical dosimetry is key for interpreting and extrapolating study results; however, dosimetry is understudied in organotypic models limiting ability to predict toxicity. We developed a dosimetry model for primary human bronchial epithelial cells (HBECs) cultured at the air-liquid interface (ALI) using benzo[a]pyrene (BAP), a representative polycyclic aromatic hydrocarbon. Dose and time course evaluation of metabolite formation and enzyme activity and expression were utilized to parameterize a cellular dosimetry model to improve the utility of ALI-HBECs for assessing chemical risk. Dosimetry analysis demonstrated absorption of BAP into cells and an increase in Phase 1 and 2 metabolites over time that correlated with regulation of metabolizing enzymes. BAP was cleared from cells by 48 h after exposure, and the primary metabolites generated in ALI-HBECs were BAP-3-phenol, BAP-4,5-dihydrodiol, BAP-7,8-dihydrodiol, BAP-9,10-dihydrodiol, BAP-7,8,9,10-tetrol, BAP-3-phenol-glucuronide, BAP-4,5-dihydrodiol-glucuronide, and BAP-9,10-dihydrodiol-glucuronide. The resulting dosimetry model described BAP and 7,8-dihydrodiol toxicokinetics in ALI-HBECs and suggested active excretion of 7,8-dihydrodiol. Overall, this study demonstrates metabolic competency of ALI-HBECs for BAP metabolism, demonstrates the usefulness of complex in vitro systems for human-relevant toxicity data, and exhibits how in silico models can be utilized for understanding the dosimetry of test compounds to aid in in vitro to human extrapolation of toxicity data for risk assessments.

Benzo[a]pyrene↗
DOE OSTI2023

exRNA-eCLIP intersection analysis reveals a map of extracellular RNA binding proteins and associated RNAs across major human biofluids and carriers

Although the role of RNA binding proteins (RBPs) in extracellular RNA (exRNA) biology is well established, their exRNA cargo and distribution across biofluids are largely unknown. To address this gap, we extend the exRNA Atlas resource by mapping exRNAs carried by extracellular RBPs (exRBPs). This map was developed through an integrative analysis of ENCODE enhanced crosslinking and immunoprecipitation (eCLIP) data (150 RBPs) and human exRNA profiles (6,930 samples). Computational analysis and experimental validation identified exRBPs in plasma, serum, saliva, urine, cerebrospinal fluid, and cell-culture-conditioned medium. exRBPs carry exRNA transcripts from small non-coding RNA biotypes, including microRNA (miRNA), piRNA, tRNA, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), Y RNA, and lncRNA, as well as protein-coding mRNA fragments. Computational deconvolution of exRBP RNA cargo reveals associations of exRBPs with extracellular vesicles, lipoproteins, and ribonucleoproteins across human biofluids. Overall, we mapped the distribution of exRBPs across human biofluids, presenting a resource for the community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Assessing the impact of human mobility to predict regional excess death in Ecuador

Abstract COVID-19 outbreaks have had high mortality in low- and middle-income countries such as Ecuador. Human mobility is an important factor influencing the spread of diseases possibly leading to a high burden of disease at the country level. Drastic control measures, such as complete lockdown, are effective epidemic controls, yet in practice one hopes that a partial shutdown would suffice. It is an open problem to determine how much mobility can be allowed while controlling an outbreak. In this paper, we use statistical models to relate human mobility to the excess death in Ecuador while controlling for demographic factors. The mobility index provided by GRANDATA, based on mobile phone users, represents the change of number of out-of-home events with respect to a benchmark date (March 2nd, 2020). The study confirms the global trend that more men are dying than expected compared to women, and that people under 30 show less deaths than expected, particularly individuals younger than 20 with a death rate reduction between 22 and 27%. The weekly median mobility time series shows a sharp decrease in human mobility immediately after a national lockdown was declared on March 17, 2020 and a progressive increase towards the pre-lockdown level within two months. Relating median mobility to excess deaths shows a lag in its effect: first, a decrease in mobility in the previous two to three weeks decreases excess death and, more novel, we found an increase of mobility variability four weeks prior increases the number of excess deaths.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Trust Your Gut: Comparing Human and Machine Inference from Noisy Visualizations

People commonly utilize visualizations not only to examine a given dataset, but also to draw generalizable conclusions about the underlying models or phenomena. Prior research has compared human visual inference to that of an optimal Bayesian agent, with deviations from rational analysis viewed as problematic. However, human reliance on non-normative heuristics may prove advantageous in certain circumstances. We investigate scenarios where human intuition might surpass idealized statistical rationality. In two experiments, we examine individuals’ accuracy in characterizing the parameters of known data-generating models from bivariate visualizations. Our findings indicate that, although participants generally exhibited lower accuracy compared to statistical models, they frequently outperformed Bayesian agents, particularly when faced with extreme samples. Participants appeared to rely on their internal models to filter out noisy visualizations, thus improving their resilience against spurious data. However, participants displayed overconfidence and struggled with uncertainty estimation. They also exhibited higher variance than statistical machines. Our findings suggest that analyst gut reactions to visualizations may provide an advantage, even when departing from rationality. These results carry implications for designing visual analytics tools, offering new perspectives on how to integrate statistical models and analyst intuition for improved inference and decision-making. The data and materials for this paper are available at https://osf.io/qmfv6

human-machine collaboration↗
DOE OSTI2025

The decay of HIV under anti-retroviral therapy is biphasic even in humanized mice with just T cells

HIV-1 plasma viral load decays in a biphasic manner during antiretroviral therapy (ART). It was hypothesized that this is due to infection of different cell types, namely CD4+ T cells and macrophages. We studied this possibility directly by modeling the decay of HIV-1 in humanized mice. We utilized previously published data from humanized T-cell only mice (TOM) and myeloid-only mice (MOM) infected with HIV-1 and treated with a potent ART regimen. Viral load decay dynamics were modeled using either a single or a biexponential decay fitted using nonlinear mixed effects techniques. Fits were compared using the corrected Bayesian information criterion (BICc). In TOM, the biphasic model was significantly better than a single-phase decay model (ΔBICc ≈ 16) despite additional parameters. In MOM, the biphasic decay was statistically better, but there was substantial uncertainty because the virus goes below detection very fast. The first-phase half-life was consistent between groups (1.2 days in MOM and 1.3 days in TOM) and similar to the half-life estimated in human infection. The second-phase decay in these mice was minimal likely due to low initial viral loads. Additional analyses with mice containing both CD4+ T cells and macrophages or X4-tropic virus-infected MOM mice confirmed the biphasic pattern, demonstrating the robustness of this result. The biphasic decline in HIV-1 occurs, even with only CD4+ T cells, refuting the hypothesis that distinct cell populations (CD4+ T cells and macrophages) drive each decay phase. These findings support an alternative model in which the observed dynamics arise from intrinsic properties of the viral infection lifecycle rather than from cellular compartmentalization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Human Performance Improvement Task Group Task 21-1 Best Practice: Using virtual capabilities or options for HPI application (to reduce errors, strengthening defenses, strengthening the organization, and/or increasing capacity)

In 2020 the world was impacted by COVID-19. How work is done was dramatically changed for a large portion of the workforce. Many have made the abrupt shift to working from their home while others have adapted to COVID protocols (such as social distancing and wearing facemasks). Fundamentally, Human and Organizational Performance Improvement concepts and science did not change – only the delivery method changed (in some cases). The primary effect has been to accelerate dynamics already present in society – from e-commerce to online education to remote healthcare. Change is never easy for humans. However, remote work should be viewed as an opportunity; not a fix to a problem. In this Best Practice paper, you’ll get practical suggestions to help you reduce errors and improve Human Performance in remote, socially-distanced “work-from-home” environments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Solutions for Enhanced Legacy Probabilistic Risk Assessment Tools and Methodologies: Improving Efficiency of Model Development and Processing via Innovative Human Reliability Dependency Analysis

Probabilistic risk assessments (PRAs) are integral to nuclear power plant (NPP) operations, having tremendously benefitted the safety of the U.S. reactor fleet for decades. Insights obtained from the models have provided perspectives on a variety of applications, both at the plant and for the regulator. While these models are very useful, they are now being asked to represent and analyze aspects of the plant that were never envisioned by the initial PRA practitioners. Furthermore, heightened demands on the PRA models have led to increased computing power requirements. Additionally, as the complexity of the PRA models increased, the difficulty experienced by non-PRA experts in trying to understand these models, grasp the insights they provide, and effectively use that information has become problematic. The need for research to address key issues regarding PRA tools and methods has never been greater. Although the nuclear power industry has largely been well-served by these tools and methods, the underlying science is dated, remaining mostly unchanged for over two decades. Three areas were identified as most beneficial to address to maintain and improve the usefulness of the current practice legacy PRA tools: improved quantification speed, increased ability to efficiently model multi-hazard models, and improved modeling human action dependency in PRA. This report is focused on the third critical area, improvements in dependency analysis of human actions conducted as part of a typical human reliability assessment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Cadmium-Free QD Building Blocks for Human Centric Lighting

This project developed Cd-free quantum dot (QD) downconverters for efficacious human-centric lighting (HCL) light emitting diode (LED) devices. Solid state HCL devices address the lack of light in the cyan wavelength region (460-490 nm) in white LEDs by enhancing the melanopic daylight efficacy ratio (MDER) value. MDER is a metric that indicates the degree to which artificial lighting stimulates nonvisual biological processes in the retina responsible for regulating circadian rhythms compared with natural lighting. The peak sensitivity of melanopsin in the retina is at 479 nm, therefore artificial lighting which can fill the well-known “cyan gap” may improve human health. Due to the Restriction of Hazardous Substances (RoHS) regulations, cadmium-free core/shell/shell QDs are the primary targets for low toxicity, tunable downconverters. Cyan- and red-emitting core/shell/shell QDs were implemented in LED devices toward achieving a brightness of 210 lm/W at 4000 K, CRI 90, and MDER > 0.7. Synthetic development of Cd-free materials yielded cyan InP/ZnS QDs with a photoluminescence quantum yield (PLQY) of ~60% between 480-490 nm, and red InP/ZnSe/(ZnSeS)/ZnS QDs reaching ~80% PLQY at 620-630 nm. We successfully demonstrated that the inclusion of cyan QDs increased the MDER value to ≥0.7, but the brightness of the HCL LED devices was hindered due to low PLQY values. However, upon substitution of the Cd-free cyan QD with a low-Cd QD with >90% PLQY, brightness improved by 25% over the Cd-free device to 179 lm/W. Despite the technical obstacles remaining toward improving emission characteristics and stability of QDs under high flux, we have confirmed the promise of narrow, tunable QD emitters in SSL packages toward the goal of healthy, human-centric lighting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Response to Influenza A Virus Infection, Processed Experimental Dataset Catalog

Influenza A virus (IAV) is a high risk biological agent, classified as a Category C priority pathogen (Orthomyxoviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), and is known to cause severe respiratory disease with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus [NCBITAXON:11320] experimental infection study. Host sample types include human lung adenocarcinoma cells ["Calu-3", BTO:0002750] and whole mouse lung [BTO:0000763] tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Response to West Nile Virus Infection, Processed Experimental Dataset Catalog

West Nile virus (WNV) is classified as a Category B priority pathogen (mosquito-borne Flavivirus) by the National Institute of Allergy and Infectious Diseases (NIAID), and are known to cause severe infections in humans where lethal host-associated mechanisms are not clearly defined. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013 - 2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding a specific West Nile virus [NCBITAXON:11082] (WNV-NY99 382) experimental infection study. Host sample types include cerebellum ["CB", BTO:0000232], cortical neurons ["CN", BTO:0004102], cortex ["CT", BTO:0000233], dendritic cells ["DC", BTO:0002042], granule cell neurons ["GCN", BTO:0003393], lymph node ["LN", BTO:0000784], and serum ["SE", BTO:0001239] from mouse (Mus musculus) tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Human Primary Airway Epithelium +/- Macrophages Response to HCoV-229E Infection Transcriptomics (ACS-DP3)

The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-299E) infection. Sample data was obtained for mock and infected (MOI 3) primary human airway epithelial cells with and without macrophages and grown in air-liquid interface conditions. Sample data was acquired using an Illumina Hi-Seq 4000 sequencer system and further processed for RNA sequencing (RNA-Seq) expression analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Methods integrating innate and adaptive immune responses in human in vitro immunization assays

Rapid vaccine development and innovative immunotherapeutics are critical in the fight against emerging outbreaks and global pandemic threats, yet the high costs and prolonged timelines for developing new vaccines underscore the urgent need for robust, predictive pre-clinical testing platforms. The rapid down-selection of vaccine candidates and identification of optimal vaccine formulations can be performed using human in vitro immunization (IVI) assays that recapitulate the complex interactions of the innate and adaptive human immune response. In this review, we present a comprehensive evaluation of three key IVI platforms: the whole blood assay (WBA), monocyte-derived dendritic cell (MoDC) assay with dendritic cell-T cell interface assay (DTI), and the microphysiological human tissue construct assay (HTC). The WBA offers a cost-effective and straightforward approach, while the MoDC + DTI system represents the current gold standard for balancing experimental efficiency with immunological complexity. The HTC assay, by mimicking both spatial and temporal aspects of immune interactions, provides enhanced physiological relevance. We discuss the methodological advantages and limitations of each platform, explore their roles in rapid vaccine candidate screening, and propose strategies for integrating these assays with complementary in vivo models. These insights pave the way for refining IVI assays and accelerating the translational pipeline for next-generation vaccines and immunotherapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗