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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Disease resistance in coral is mediated by distinct adaptive and plastic gene expression profiles

Infectious diseases are an increasing threat to coral reefs, resulting in altered community structure and hindering the functional contributions of disease-susceptible species. We exposed seven reef-building coral species from the Caribbean to white plague disease and determined processes involved in (i) lesion progression, (ii) within-species gene expression plasticity, and (iii) expression-level adaptation among species that lead to differences in disease risk. Gene expression networks enriched in immune genes and cytoskeletal arrangement processes were correlated to lesion progression rates. Whether or not a coral developed a lesion was mediated by plasticity in genes involved in extracellular matrix maintenance, autophagy, and apoptosis, while resistant coral species had constitutively higher expression of intracellular protein trafficking. This study offers insight into the process involved in lesion progression and within- and between-species dynamics that lead to differences in disease risk that is evident on current Caribbean reefs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.)

Active breeding programs specifically for root system architecture (RSA) phenotypes remain rare; however, breeding for branch and taproot types in the perennial crop alfalfa is ongoing. Phenotyping in this and other crops for active RSA breeding has mostly used visual scoring of specific traits or subjective classification into different root types. While image-based methods have been developed, translation to applied breeding is limited. This research is aimed at developing and comparing image-based RSA phenotyping methods using machine and deep learning algorithms for objective classification of 617 root images from mature alfalfa plants collected from the field to support the ongoing breeding efforts. Our results show that unsupervised machine learning tends to incorrectly classify roots into a normal distribution with most lines predicted as the intermediate root type. Encouragingly, random forest and TensorFlow-based neural networks can classify the root types into branch-type, taproot-type, and an intermediate taproot-branch type with 86% accuracy. With image augmentation, the prediction accuracy was improved to 97%. Coupling the predicted root type with its prediction probability will give breeders a confidence level for better decisions to advance the best and exclude the worst lines from their breeding program. This machine and deep learning approach enables accurate classification of the RSA phenotypes for genomic breeding of climate-resilient alfalfa.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Growing grasses in unprofitable areas of US Midwest croplands could increase species richness

The US has large potential to grow perennial energy crops, but because these crops are rarely grown in current agricultural landscapes, it is unclear how biodiversity may be affected. Over time, as agriculture has increased, many grassland species have declined. In addition, not all agricultural land is profitable for growing annual crops. Unprofitable areas were responsible for a loss of approximately $110 million USD per year from 2013 to 2016. Based on this, we want to know how converting less-profitable portions of agricultural fields to switchgrass, a native prairie grass, would influence species occurrence. To address this question, we developed an alternative landscape in which clustered corn/soy acres with a low return on investment (ROI) were replaced with grassland. We also developed and validated species distribution models to predict changes in species occurrence for 28 avian species in Iowa in response to landscape management. Furthermore, we compared results for three different models: Random forest (RF), Stochastic gradient boosting (GBM), and Neural network (Nnet) and found that all models performed well and predicted similar species distribution. Predicted species richness increased by 3.66% (RF), 2.79% (GBM), and 7.51% (Nnet) when we simulated a change in management for ~3% of Iowa's low ROI corn/soybean areas to grassland. If harvested, these areas could generate approximately 7.6 million dry tons/year of switchgrass for bioenergy, thereby increasing farmers earnings. Unprofitable areas tended to occur along streams, which suggest that incorporating partially harvested riparian buffers can benefit avian biodiversity, while improving water quality and reducing unnecessary costs for farmers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

CyanoCyc cyanobacterial web portal

CyanoCyc is a web portal that integrates an exceptionally rich database collection of information about cyanobacterial genomes with an extensive suite of bioinformatics tools. It was developed to address the needs of the cyanobacterial research and biotechnology communities. The 277 annotated cyanobacterial genomes currently in CyanoCyc are supplemented with computational inferences including predicted metabolic pathways, operons, protein complexes, and orthologs; and with data imported from external databases, such as protein features and Gene Ontology (GO) terms imported from UniProt. Five of the genome databases have undergone manual curation with input from more than a dozen cyanobacteria experts to correct errors and integrate information from more than 1,765 published articles. CyanoCyc has bioinformatics tools that encompass genome, metabolic pathway and regulatory informatics; omics data analysis; and comparative analyses, including visualizations of multiple genomes aligned at orthologous genes, and comparisons of metabolic networks for multiple organisms. CyanoCyc is a high-quality, reliable knowledgebase that accelerates scientists’ work by enabling users to quickly find accurate information using its powerful set of search tools, to understand gene function through expert mini-reviews with citations, to acquire information quickly using its interactive visualization tools, and to inform better decision-making for fundamental and applied research.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Integrins, tensegrity, and mechanotransduction

Physical forces, such as those due to gravity, play an important role in tissue development and remodeling. Yet, little is known about how individual cells sense mechanical signals or how they transduce them into a chemical response. Rather than listing the numerous signal pathways that have been found to be sensitive to mechanical stimulation, we need to place potential molecular signaling mechanisms within the context of the entire cell. The model presented is based on the concept that cells use tensegrity architecture to organize their cytoskeleton and stabilize their form. Studies with stick and string tensegrity cell models predict that living cells are hard-wired to respond immediately to external mechanical stresses. This hard-wiring exists in the form of discrete cytoskeletal filament networks that mechanically couple specific cell surface receptors, such as integrins, to nuclear matrix scaffolds and to potential transducing molecules that physically associate with the cytoskeleton. If these signaling molecules do function in a "solid-state", then mechanical stresses may be transduced into biochemical responses through force-dependent changes in cytoskeletal geometry or through local alterations in thermodynamic or kinetic parameters. Changes in cytoskeletal tension (prestress) also may play a role in signal amplification and adaptation. Recent experimental results are described which provide direct support for the tensegrity theory.

Review↗
DOE OSTI2022

Targeting KDM4 for treating PAX3-FOXO1–driven alveolar rhabdomyosarcoma

Chimeric transcription factors drive lineage-specific oncogenesis but are notoriously difficult to target. Alveolar rhabdomyosarcoma (RMS) is an aggressive childhood soft tissue sarcoma transformed by the pathognomonic Paired Box 3–Forkhead Box O1 (PAX3-FOXO1) fusion protein, which governs a core regulatory circuitry transcription factor network. Here, we show that the histone lysine demethylase 4B (KDM4B) is a therapeutic vulnerability for PAX3-FOXO1 + RMS. Genetic and pharmacologic inhibition of KDM4B substantially delayed tumor growth. Suppression of KDM4 proteins inhibited the expression of core oncogenic transcription factors and caused epigenetic alterations of PAX3-FOXO1–governed superenhancers. Combining KDM4 inhibition with cytotoxic chemotherapy led to tumor regression in preclinical PAX3-FOXO1 + RMS subcutaneous xenograft models. In summary, we identified a targetable mechanism required for maintenance of the PAX3-FOXO1–related transcription factor network, which may translate to a therapeutic approach for fusion-positive RMS.

Cell Biology↗
DOE OSTI2025

2024 Results for Avian Monitoring at the Technical Area 36 Minie Site, Technical Area 39 Point 6, Technical Area 16 Burn Ground, and DARHT at Los Alamos National Laboratory

Los Alamos National Laboratory (LANL) biological subject matter experts in the Environmental Protection and Compliance Division initiated a multi-year program in 2013 to monitor avifauna (birds) at two open detonation sites and one open burn site on LANL property. Additional monitoring began in 2017 at a third firing site, the Dual-Axis Radiographic Hydrodynamic Test (DARHT) Facility. In this annual report, we compare monitoring results from these efforts among years to identify and evaluate firing and open burn site impacts on the local bird community. The objectives of this study are • to determine whether LANL operations impact bird abundance, species richness, or diversity; • to examine occupancy and nest success of secondary-cavity nesting birds that use nest boxes; and • to examine chemical concentrations (such as radionuclides, inorganic elements, and/or organic compounds) in nonviable eggs and deceased nestlings that are collected opportunistically with the upper-level bounds of background concentrations, when available. During May through July 2024, LANL biologists completed multiple avian point count surveys at each of the following treatment sites: • Technical Area (TA) 36 Minie Site, • TA-39 Point 6, • TA-16 Burn Ground, and • DARHT. We recorded a total of 1,088 birds that represented 65 species at the four treatment sites and compared these results with data from their associated control sites. In 2024, abundance and species richness at treatment and control sites continued to trend similarly from year to year, with minor random deviations expected from bird communities. Species richness at firing sites differed little from the previous year’s values. Two new bird species were observed at the firing sites—cedar waxwing (Bombycilla cedrorum) and pinyon jay (Gymnorhinus cyanocephalus). Shannon diversity values at TA-36 Minie Site, TA-39, and DARHT were statistically higher than one or more of their associated controls. Annual species diversity at treatment sites was high in 2024 across all firing sites relative to similar habitat control sites. We also monitored avian nest boxes to compare occupancy and nest success data from nest boxes at treatment sites with the overall avian nest box monitoring network and against a subset of relevant control sites. Nest box success has decreased at both treatment and control sites since monitoring began, suggesting that overlapping climatic factors are responsible for patterns of declining nest success. In 2024, nonviable avian eggs and one nestling were opportunistically collected at Bandelier National Monument, TA-16 Burn Ground, TA-36 Minie, TA-39 Point 6, and DARHT. All egg samples and the one nestling sample were evaluated for per- and polyfluoroalkyl substances, which were detected from all locations, including the control site at Bandelier National Monument. Overall results from 2024 continue to suggest that operations at the four treatment sites are not negatively impacting bird populations. This long-term project will continue to monitor for any changes over time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Nramp: Deprive and conquer?

Solute carriers 11 (Slc11) evolved from bacterial permease (MntH) to eukaryotic antibacterial defense (Nramp) while continuously mediating proton (H+)-dependent manganese (Mn2+) import. Also, Nramp horizontal gene transfer (HGT) toward bacteria led to mntH polyphyly. Prior demonstration that evolutionary rate-shifts distinguishing Slc11 from outgroup carriers dictate catalytic specificity suggested that resolving Slc11 family tree may provide a function-aware phylogenetic framework. Hence, MntH C (MC) subgroups resulted from HGTs of prototype Nramp (pNs) parologs while archetype Nramp (aNs) correlated with phagocytosis. PHI-Blast based taxonomic profiling confirmed MntH B phylogroup is confined to anaerobic bacteria vs. MntH A (MA)’s broad distribution; suggested niche-related spread of MC subgroups; established that MA-variant MH, which carries ‘eukaryotic signature’ marks, predominates in archaea. Slc11 phylogeny shows MH is sister to Nramp. Site-specific analysis of Slc11 charge network known to interact with the protonmotive force demonstrates sequential rate-shifts that recapitulate Slc11 evolution. 3D mapping of similarly coevolved sites across Slc11 hydrophobic core revealed successive targeting of discrete areas. The data imply that pN HGT could advantage recipient bacteria for H+-dependent Mn2+ acquisition and Alphafold 3D models suggest conformational divergence among MC subgroups. It is proposed that Slc11 originated as a bacterial stress resistance function allowing Mn2+-dependent persistence in conditions adverse for growth, and that archaeal MH could contribute to eukaryogenesis as a Mn2+ sequestering defense perhaps favoring intracellular growth-competent bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory

X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray μCT images, using low-cost resources in Google’s Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Photosynthetic Electron Flows and Networks of Metabolite Trafficking to Sustain Metabolism in Photosynthetic Systems

Photosynthetic eukaryotes have metabolic pathways that occur in distinct subcellular compartments. However, because metabolites synthesized in one compartment, including fixed carbon compounds and reductant generated by photosynthetic electron flows, may be integral to processes in other compartments, the cells must efficiently move metabolites among the different compartments. This review examines the various photosynthetic electron flows used to generate ATP and fixed carbon and the trafficking of metabolites in the green alga Chlamydomomas reinhardtii; information on other algae and plants is provided to add depth and nuance to the discussion. We emphasized the trafficking of metabolites across the envelope membranes of the two energy powerhouse organelles of the cell, the chloroplast and mitochondrion, the nature and roles of the major mobile metabolites that move among these compartments, and the specific or presumed transporters involved in that trafficking. These transporters include sugar-phosphate (sugar-P)/inorganic phosphate (Pi) transporters and dicarboxylate transporters, although, in many cases, we know little about the substrate specificities of these transporters, how their activities are regulated/coordinated, compensatory responses among transporters when specific transporters are compromised, associations between transporters and other cellular proteins, and the possibilities for forming specific ‘megacomplexes’ involving interactions between enzymes of central metabolism with specific transport proteins. Finally, we discuss metabolite trafficking associated with specific biological processes that occur under various environmental conditions to help to maintain the cell’s fitness. These processes include C4 metabolism in plants and the carbon concentrating mechanism, photorespiration, and fermentation metabolism in algae.

Plant Sciences↗
DOE OSTI2020

Roles of D1-Glu189 and D1-Glu329 in O 2 Formation by the Water-Splitting Mn 4 Ca Cluster in Photosystem II

During the catalytic step that precedes O–O bond formation in Photosystem II, a water molecule deprotonates and moves next to the water-splitting Mn 4 Ca cluster’s O5 oxo bridge. The relocated oxygen, known as O6 or Ox, may serve as a substrate, combining with O5 to form O 2 during the final step in the catalytic cycle, or may be positioned to become a substrate during the next catalytic cycle. Recent serial femtosecond X-ray crystallographic studies show that the flexibility of D1-E189 plays a critical role in facilitating the relocation of O 6 /Ox. In this study, the D1-E189G and D1-E189S mutations were characterized with FTIR difference spectroscopy. The data show that both mutations support Mn 4 Ca cluster assembly, substantially inhibit advancement beyond the S 2 state, and alter the network of H bonds that surrounds the Mn 4 Ca cluster. Previously, the D1-E189Q, D1-E189K, and D1-E189R mutations were shown to have little impact on the activity, electron transfer rates, or spectral properties of Photosystem II. A rationale for this behavior is presented. The residue D1-E329 interacts with water molecules in the O1 water network that has been suggested recently to supply substrate during the catalytic cycle. Characterization of the D1-E329A mutant with FTIR difference spectroscopy shows that this mutation does not substantially perturb the structure of PSII or the water molecules whose O–H stretching modes change during the catalytic cycle. Furthermore, this result provides additional evidence that the water molecules whose vibrational properties change during the S 1 to S 2 transition are confined approximately to the region bounded by D1-N87, D1-N298, and D2-K317.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A native IgE in complex with profilin provides insights into allergen recognition and cross-reactivity

Allergies have become a rising health problem, where plentiful substances can trigger IgE-mediated allergies in humans. While profilins are considered minor allergens, these ubiquitous proteins are primary molecules involved in cross-reactivity and pollen-food allergy syndrome. Here we report the first crystal structures of murine Fab/IgE, with its chains naturally paired, in complex with the allergen profilin from Hevea brasiliensis (Hev b 8). The crystallographic models revealed that the IgE’s six complementarity-determining regions (CDRs) interact with the allergen, comprising a rigid paratope-epitope surface of 926 Å 2 , which includes an extensive network of interactions. Interestingly, we also observed previously unreported flexibility at Fab/IgE’s elbow angle, which did not influence the shape of the paratope. The Fab/IgE exhibits a high affinity for Hev b 8, even when using 1 M NaCl in BLI experiments. Finally, based on the encouraging cross-reactivity assays using two mutants of the maize profilin (Zea m 12), this antibody could be a promising tool in IgE engineering for diagnosis and research applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Toward wide-spectrum antivirals against coronaviruses: Molecular characterization of SARS-CoV-2 NSP13 helicase inhibitors

To date, effective therapeutic treatments that confer strong attenuation against coronaviruses (CoVs) remain elusive. Among potential drug targets, the helicase of CoVs is attractive due to its sequence conservation and indispensability. We rely on atomistic molecular dynamics simulations to explore the structural coordination and dynamics associated with the SARS-CoV-2 Nsp13 apo enzyme, as well as their complexes with natural ligands. A complex communication network is revealed among the five domains of Nsp13, which is differentially activated because of the presence of the ligands, as shown by shear strain analysis, principal components analysis, dynamical cross-correlation matrix analysis, and water transport analysis. The binding free energy and the corresponding mechanism of action are presented for three small molecules that were shown to be efficient inhibitors of the previous SARS-CoV Nsp13 enzyme. Together, our findings provide critical fresh insights for rational design of broad-spectrum antivirals against CoVs.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2008

The Use of Simulated Visible/Infrared Imager/Radiometer Suite (VIIRS) and Landsat Data Continuity Mission (LDCM) Imagery for Coral Reef Monitoring

Coral reefs are some of the most biologically rich and economically important ecosystems on Earth. Coral reefs are Earth's largest biological structures and have taken thousands of years to form. Coral reefs not only provide important habitat for many marine animals and plants, but they also provide humanity with food, jobs, chemicals, protection against storms, and life-saving pharmaceuticals. Severe bleaching events have occurred that have dramatic long-term ecological impacts to corals, including loss of reef-building corals, changes in benthic habitat, and, in some cases, changes in larval fish populations (Holden and Ledrew, 1998). Some researchers suggest that 10 percent of Earth s coral reefs have already been destroyed and that another 60 percent are in danger. Scientists have proposed that as much as 95 percent of Jamaica's reefs are dying or dead. This poster reports on a Rapid Prototyping Capability (RPC) experiment done to determine whether future NASA sensors - the Visible/Infrared Imager/Radiometer Suite (VIIRS) and Landsat Data Continuity Mission (LDCM) - could generate key data products for the Integrated Coral Reef Observation Network (ICON)/Coral Reef Early Warning System (CREWS) Decision Support Tool (DST) operated by the National Oceanic and Atmospheric Administration (NOAA).

Estep, L.↗
NASA NTRSDate not supplied

High Sensitive and Low Power Nanosensors for Space and Terrestrial Applications

Nanotechnology offers the ability to work at the molecular level, atom by atom, to create large structures with fundamentally new molecular organization. It is essentially concerned with materials, devices, and systems whose structures and components exhibit novel and significantly improved physical, chemical and biological properties, phenomena, and process control due to their nanoscale size. A nanosensor technology has been developed at NASA Ames using nanostructure, single walled carbon nanotubes (SWNTs). The nanosensors have achieved low detection limit of chemicals in the concentration range of ppm to ppb. Due to large surface area, low surface energy barrier and high thermal and mechanical stability, nanostructured chemical sensors offer higher sensitivity, lower power consumption and a more robust solution than most state-of-the-art systems making them attractive for space and terrestrial applications. An example of a sensor module, the first space flown nano device, will be introduced in this presentation. Such sensors have drawn attention from space community for global weather monitoring, space exploration, life search in the universe, and launch pad fuel leak detection and in-flight cabin air and life support system monitoring, and engine operation monitoring. Additionally, the wireless capability of such sensors can be leveraged to network mobile and fixed-base detection and warning systems for civilian population centers, military bases and battlefields, as well as other high-value or high-risk assets and areas in industry.

Jing Li↗
DOE OSTI2022

Integrating phytoplankton pigment and DNA meta-barcoding observations to determine phytoplankton composition in the coastal ocean

Quantifying phytoplankton composition is critical to predicting marine ecosystem structure and function. DNA meta-barcoding and high-performance liquid chromatography (HPLC) pigment analysis are two widely used methods for assessing phytoplankton composition; however, comparing their performance has been done only rarely. Here, we integrate DNA meta-barcoding and HPLC pigment observations to determine eukaryotic phytoplankton composition in the Santa Barbara Channel, California. We find that both methods identify the same four dominant eukaryotic phytoplankton taxa (diatoms, dinoflagellates, chlorophytes, and prymnesiophytes), but inter- and intra-lineage variability in biomarker pigmentation (associated with both a lack of taxonomic specificity of biomarker pigments and intrinsic differences in accessory pigmentation) drives substantial disagreement between the methods. Covariation network analysis circumvents this disagreement and reveals that diverse assemblages of phytoplankton and other protists covary with distinct suites of biomarker pigments. Our results highlight the strengths and weaknesses of each method in characterizing phytoplankton composition and reveal novel insights into phytoplankton physiology that could only be gained by integrating the two methods. Finally, we suggest a path to monitor eukaryotic plankton communities on unprecedented spatiotemporal scales based on the covariation of unique phytoplankton and protistan assemblages with remotely sensible phytoplankton pigment concentrations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

BioSentinel: To the Moon or Beyond?

BioSentinel, an Artemis-1 secondary spacecraft, will carry a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft and included technologies newly developed or adapted for operations beyond Earth orbit. This is the maiden deep-space voyage for the radio, propulsion system, electrical power system, and BioSensor payload. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. Flying a secondary payload beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. BioSentinel does not carry propulsion for trajectory maneuvers, so plans for Comms and Power need to be developed for all trajectories. The nominal plan is a lunar flyby followed by an insertion into Heliocentric orbit. However, some possible scenarios include lunar eclipses that could severely impact the power budget during that phase of the mission, while others could result in a “Retrograde” hyperbola at swingby resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. BioSentinel’s final trajectory will not be known until after launch and deployment so possible scenarios need to be planned for ahead of time. This paper discusses the operational scenarios that were planned for as well as the actual execution of the mission operations including: command pass scheduling with the Deep Space Network, selecting bandwidth limits, medium gain antenna versus low gain antenna usage, and conserving power prior to a lunar eclipse. Note: Artemis-1 is planned to launch in the Spring of 2022

BioSentinel↗