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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Functional characterization of a cellulose synthase, CtCESA1, from the marine red alga Calliarthron tuberculosum (Corallinales)

In land plants and algae, cellulose is important for strengthening cell walls and preventing breakage due to physical forces. Though our understanding of cellulose production by cellulose synthases (CESAs) has seen significant advances for several land plant and bacterial species, functional characterization of this fundamental protein is absent in red algae. Here we identify CESA gene candidates in the calcifying red alga Calliarthron tuberculosum using sequence similarity-based approaches, and elucidate their phylogenetic relationship with other CESAs from diverse taxa. One gene candidate, CtCESA1, was closely related to other putative red algal CESA genes. To test if CtCESA1 encoded a true cellulose synthase, CtCESA1 protein was expressed and purified from insect and yeast expression systems. CtCESA1 showed glucan synthase activity in glucose tracer assays. CtCESA1 activity was relatively low when compared with plant and bacterial CESA activity. In an in vitro assay, a predicted N-terminal starch-binding domain from CtCESA1 bound red algal floridean starch extracts, representing a unique domain in red algal CESAs not present in CESAs from other lineages. When the CtCESA1 gene was introduced into Arabidopsis thaliana cesa mutants, the red algal CtCESA1 partially rescued the growth defects of the primary cell wall cesa6 mutant, but not cesa3 or secondary cell wall cesa7 mutants. A fluorescently tagged CtCESA1 localized to the plasma membrane in the Arabidopsis cesa6 mutant background. This study presents functional evidence validating the sequence annotation of red algal CESAs. Furthermore, the relatively low activity of CtCESA1, partial complementation in Arabidopsis, and presence of unique protein domains suggest that there are probably functional differences between the algal and land plant CESAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Disturbed, diffuse, or just missing? A global study of the H I content of Hickson compact groups

Hickson compact groups (HCGs) are dense configurations of four to ten galaxies, whose H I morphology appears to follow an evolutionary sequence of three phases, with gas initially confined to galaxies, then significant amounts spread throughout the intra-group medium, and finally with almost no gas remaining in the galaxies themselves. It has also been suggested that several groups may harbour a diffuse H I component that is resolved out by interferometric observations. The H I deficiency of HCGs is expected to increase as the H I morphological phase progresses along the evolutionary sequence. If this is the case, H I deficiency would be a rough proxy for the age and evolutionary state of a HCG. We aim to test this hypothesis for the first time using a large sample of HCGs and to investigate the evidence for diffuse H I in HCGs. We performed a uniform reduction of all publicly available VLA H I observations (38 HCGs) with a purpose-built pipeline that also maximises the reproducibility of this study. The resulting H I data cubes were then analysed with the latest software tools to perform a manual separation of emission features into those belonging to galaxies and those extending into the intra-group medium. We thereby classified the H I morphological phase of each group as well as quantified their H I deficiency compared to galaxies in isolation. We find little evidence that H I deficiency can be used as a proxy for the evolutionary phase of a compact group in either of the first two phases, with the distribution of H I deficiency being consistent in both. However, for the final phase, the distribution clearly shifts to high H I deficiencies, with more than 90% of the expected H I content typically missing. Across all HCGs studied, we identify a few cases where there is strong evidence for a diffuse gas component in the intra-group medium, which might be detectable with improved observations. We also classify a new sub-phase where groups contain a lone H I -bearing galaxy, but are otherwise devoid of gas. The new morphological phase we have identified is likely the result of an evolved, gas-poor group acquiring a new, gas-rich member. The large spread of H I deficiencies in the first two morphological phases suggests that there is a broad range of initial H I content in HCGs, which is perhaps influenced by large-scale environment, and that the timescale for morphological changes is, in general, considerably shorter than the timescale for the destruction or consumption of neutral gas in these systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Strangers in a foreign land: ‘Yeastizing’ plant enzymes

Abstract Expressing plant metabolic pathways in microbial platforms is an efficient, cost‐effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here, we first summarize the current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labour‐intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost‐effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data‐driven machine learning framework designed to extract ‘yeastizing’ rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design‐build‐test cycle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Machine learning-based inversion for acoustic impedance with large synthetic training data: Workflow and data characterization

Where wells are sparse or training data are difficult to label with high-quality wireline-derived impedance logs, machine learning (ML)-based inversion of acoustic impedance typically depends on small training data sets, leading to biased prediction. We have advanced a novel workflow that applies large synthetic seismic training data to reduce facies-related bias. Using a geologically realistic model as the truth model, we randomly select sparse seed wells to perform sequential Gaussian simulation (SGS) for impedance models of the same geometry and simulate facies variability. We implement random forest regression on 30 features extracted from the synthetic volume. We observe that more seed wells tend to reduce facies-induced bias by sampling more types of facies, resulting in a better prediction. We then focus on the responses of SGS models to facies changes, the number of seed wells necessary for a useful synthetic model, and how much a synthetic model can help ML-based inversion. Here, we observe that the SGS synthetic training model outperforms well-direct training in general. For modeled clastic shore-zone systems in Miocene Gulf of Mexico, two or more seed wells are necessary for a significant reduction of root-mean-square error and outliners, and improvement of facies imaging. In a field-data test, we apply a similar workflow to quantitatively predict acoustic impedance, which is then converted to a sand-volume map at a high-frequency sequence (10–100 m), revealing detailed facies and sandstone patterns. Such results are valuable in many geologic and engineering applications, such as hydrocarbon and CO 2 reservoir prospecting, reserve estimation, simulation, etc.

3D seismic↗
DOE OSTI2024

Experimental Validation of Thermal Hydraulic Behavior in Sodium Fast Reactors (SFR) with the Thermal Hydraulic Experimental Test Article (THETA)

Thermal stratification and transition to natural circulation pose two of the largest sources of uncertainty in systems-level modeling of liquid metal-cooled fast reactors. As these phenomena typically develop during transient event sequences, licensing-basis events analyzed using systemslevel models may have considerable uncertainties associated with thermal-hydraulic parameters of the system to account for these phenomena. As a result, the validation basis for these phenomena for systems-level codes is insufficient to fully support the wide range of liquid metal fast reactors being developed in the US. Currently, the most viable path for licensing a design is to take significant conservatisms and maintain sufficiently large safety margins to account for this uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Cyber Attack Sequences Generation for Electric Power Grid

Security assessment of cyber-physical energy systems (CPESs) such as the electric power grid is a critical operation to maintain availability, reliability, and quality of service in the presence of persistent threats from malicious cyber actors. Existing security assessment approaches such as penetration testing and red teaming rely on subject matter expert experience and forensic cyber analysis of historical events to perform realistic, threat-informed assessments of CPES defense. CPESs have a large attack surface because of the heterogeneity and complexity of underlying topology, devices, measurements, and vulnerabilities. The aforementioned approaches lead to partial coverage of the attack surface with a large set of unknown but possible exploits. There is a need to automate the CPES attack surface discovery and contextualize it for relevant, highly probable, real-world attack scenarios. We propose a methodology and framework to facilitate the discovery of the CPES attack surface. We present a multilayer attack graph with ranked attack sequences to describe CPES failure scenarios. We present a work-in-progress framework that lists key components to automate the attack modeling and sequence generation. We demonstrate the published National Electric Sector Cybersecurity Organization Resource CPES failure scenario to highlight the trustworthiness of generated attack sequences.

Dutta, Ashutosh↗
DOE OSTI2024

Long-term effects of cycle time and volume exchange ratio on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) production from food waste digestate by Haloferax mediterranei cultivated in sequencing batch reactors for 450 days

Food waste digestate was fed into a sequencing batch reactor (SBR) for Haloferax mediterranei (HM) to produce poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV). This SBR was operated uninterruptedly for 450 days to test its stability, during which the cycle time and volume exchange ratio were varied to understand their impacts on the PHBV fermentation performance under ranged organic loading rates (OLR). Results showed that 1) PHBV productivity was proportional to OLR of food waste digestate; 2) substrate and product inhibitions were two limiting factors constraining substrate utilization and PHBV yields; 3) PHBV titer was dependent on the hydraulic retention time of the SBR while a volume exchange ratio lower than 0.5 is unfavorable due to the product inhibitor accumulation. Furthermore, this study for the first time demonstrated that the long-term stability of food waste-fed PHBV production by HM and revealed that inhibition effects could be barriers in SBR limiting the full-scale application of the technology.

09 BIOMASS FUELS↗
DOE OSTI2025

The glass-ceiling convective regime and the origin and diversity of coronae on Venus

Venus and Earth are rocky planets of roughly the same size and bulk density, yet their surface volcanic and tectonic features appear substantially different. On Venus, the coexistence of large volcanic highlands—interpreted as the surface expression of long-lived mantle plumes—alongside coronae, smaller features thought to be caused by transient thermal diapirs, remains enigmatic. Using two-dimensional numerical models of mantle convection with sharp and broad mineral phase transitions for pyrolite, we show that both scales of upwellings can be generated in a stagnant lid planet with an interior temperature 250 to 400 K warmer than Earth’s. The smaller plumes originate from a ~600 km deep internal layer that exists as a consequence of the different sequence of mineral phase transitions that occur in warmer mantles less processed and differentiated by partial melting and volcanism. Future models that include melting will provide further tests of our hypothesis.

Science & Technology - Other Topics↗
DOE OSTI2024

Efficient species identification for Pacific salmon genetic monitoring programs

Abstract Genetic monitoring of Pacific salmon in the Columbia River basin provides crucial information to fisheries managers that is otherwise challenging to obtain using traditional methods. Monitoring programs such as genetic stock identification (GSI) and parentage‐based tagging (PBT) involve genotyping tens of thousands of individuals annually. Although rare, these large sample collections inevitably include misidentified species, which exhibit low genotyping success on species‐specific Genotyping‐in‐Thousands by sequencing (GT‐seq) panels. For laboratories involved in large‐scale genotyping efforts, diagnosing non‐target species and reassigning them to the appropriate monitoring program can be costly and time‐consuming. To address this problem, we identified 19 primer pairs that exhibit consistent cross‐species amplification among salmonids and contain 51 species informative variants. These genetic markers reliably discriminate among 11 salmonid species and two subspecies of Cutthroat Trout and have been included in species‐specific GT‐seq panels for Chinook Salmon, Coho Salmon, Sockeye Salmon, and Rainbow Trout commonly used for Pacific salmon genetic monitoring. The majority of species‐informative amplicons (16) were newly identified from the four existing GT‐seq panels, thus demonstrating a low‐cost approach to species identification when using targeted sequencing methods. A species‐calling script was developed that is tailored for routine GT‐seq genotyping pipelines and automates the identification of non‐target species. Following extensive testing with empirical and simulated data, we demonstrated that the genetic markers and accompanying script accurately identified species and are robust to missing genotypic data and low‐frequency, shared polymorphisms among species. Finally, we used these tools to identify Coho Salmon incidentally caught in the Columbia River Chinook Salmon sport fishery and used PBT to determine their hatchery of origin. These molecular and computing resources provide a valuable tool for Pacific salmon conservation in the Columbia River basin and demonstrate a cost‐effective approach to species identification for genetic monitoring programs.

Robinson, Zachary L.↗
DOE OSTI2021

A Two-Step PCR Protocol Enabling Flexible Primer Choice and High Sequencing Yield for Illumina MiSeq Meta-Barcoding

High-throughput amplicon sequencing that primarily targets the 16S ribosomal DNA (rDNA) (for bacteria and archaea) and the Internal Transcribed Spacer rDNA (for fungi) have facilitated microbial community discovery across diverse environments. A three-step PCR that utilizes flexible primer choices to construct the library for Illumina amplicon sequencing has been applied to several studies in forest and agricultural systems. The three-step PCR protocol, while producing high-quality reads, often yields a large number (up to 46%) of reads that are unable to be assigned to a specific sample according to its barcode. Here, we improve this technique through an optimized two-step PCR protocol. We tested and compared the improved two-step PCR meta-barcoding protocol against the three-step PCR protocol using four different primer pairs (fungal ITS: ITS1F-ITS2 and ITS1F-ITS4, and bacterial 16S: 515F-806R and 341F-806R). We demonstrate that the sequence quantity and recovery rate were significantly improved with the two-step PCR approach (fourfold more read counts per sample; determined reads ≈90% per run) while retaining high read quality (Q30 > 80%). Given that synthetic barcodes are incorporated independently from any specific primers, this two-step PCR protocol can be broadly adapted to different genomic regions and organisms of scientific interest.

16S rDNA↗
DOE OSTI2024

Laser micro-machining and damage testing of rounded shadow cone blockers on silica glass for arresting laser damage growth by redirection of light

Structured conical blockers manufactured on optical input surfaces are being used to shadow, and thereby, arrest growth of exit surface damage on large optics for applications in high-energy laser systems to extend their lifetime usage. However, as the size of the Shadow Cone Blocker (SCB) is increased, the deflected light must be carefully managed to prevent consequential damage from downstream intensification. Here, we design and fabricate a distinct input SCB geometry to alleviate this problem, enabling larger damage site mitigation. The demonstrated ~1 mm diameter SCB was manufactured with a convergent approach using a CO 2 pulsed laser ablative scanning sequence on a fused silica window. The SCB design was refined to maximize resistance to both input and exit surface damage initiations on 1 cm thick fused silica windows when exposed to 351 nm irradiation and validated with laser damage testing. The design showed to prevent damage onset to the exit surface for incident fluences on the SCB of 10.7 ± 1.3 J·cm -2 and is resistant to damage on the input surface exceeding 30 J·cm -2 input fluence.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian estimation of HIV acquisition dates for prevention trials

Accurate timing estimates of when participants acquire HIV in HIV prevention trials are necessary for determining antibody levels at acquisition. The Antibody-Mediated Prevention (AMP) Studies showed that a passively administered broadly neutralizing antibody can prevent the acquisition of HIV from a neutralization-sensitive virus. We developed a pipeline for estimating the date of detectable HIV acquisition (DDA) in AMP Study participants using diagnostic and viral sequence data. Using a Bayesian strategy that combines three streams of data (REN [rev/vpu/env/Δnef] sequence, GP [gag/Δpol] sequence, and diagnostic) where their 95% credible intervals overlap based on pre-specified criteria and decision rules. We evaluated the performance of our AMP pipeline using PacBio viral sequence data from 41 participants across two prospective acute HIV acquisition cohort studies, FRESH and RV217, with twice-weekly sampling. These cohort studies enrolled young women in South Africa and men and women in Kenya and Thailand, respectively, with a high likelihood of HIV acquisition. In evaluating performance, “true DDA” was the center of bounds between last-negative and first-positive RNA diagnostic tests (median time 4 days, range 2–7 days); bias was the mean difference between estimated and true DDA. Using diagnostic data alone yielded timing estimates with a bias of 2.4 days and root mean square error (RMSE) of 7.9 days. These results were improved using sequence + diagnostic data (bias 1.5 days, RMSE 6.9 days), as well as by restricting sequence-based estimation to samples from ≤5 weeks post-DDA (bias 0.2 days, RMSE 7.8 days).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Test Bed for Evaluating Frequency Estimation Algorithms in Synthetic Inertia Control: User Manual

As penetration of converter interfaced generators (CIGs) increases, the need for CIG frequency control participation increases. Traditionally, research in this area has been performed using positive sequence simulation software, which provides voltage magnitude and phase measurements, but not point-on-wave (POW) measurements. This means that the effect of frequency estimation algorithms cannot be accurately modeled, especially when the voltage waveform is distorted by faults or load connection events. This report serves as a user manual for an electromagnetic transient simulation testbed, which allows for accurate modeling of frequency estimation and control techniques.

42 ENGINEERING↗
DOE OSTI2023

A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism

Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R2 value of 0.54, while predictions based on pFBA had an inferior R2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2’s flux predictions display a high R2 of 0.96 while pFBA showed an R2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.

Roell, Garrett W.↗
DOE OSTI2023

Fecal microbiota transplantation ameliorates type 2 diabetes via metabolic remodeling of the gut microbiota in db/db mice

Gut microbiome (GM) deregulation has been implicated in major conditions such as obesity and type 2 diabetes (T2DM). Our previous prospective study indicated that fecal microbiota transplantation (FMT) successfully improved patients with T2DM. We hypothesized that FMT may be a potential therapeutic method for T2DM, but its precise mechanisms in T2DM remains to be elucidated. Eight db/m mice were FMT donors and control mice, and 16 genetically diabetic db/db mice were equally divided into two groups (db/db+phosphate-buffered saline (PBS) group, db/db+FMT group). The db/db+FMT group was administered fresh fecal suspension (0.2 mL/mice) daily for 4 weeks. Analysis of the GM and serum metabolome was carried out by 16S ribosomal RNA sequencing and liquid chromatogram-mass spectrometry, respectively. Effects of FMT on the gut barrier and pancreas were assessed using protein assays, messenger RNA, immunohistology and clinical indicators testing. Our results showed that FMT treatment of db/db mice relieves a series of clinical indicators, including fasting plasma glucose, serum insulin and oral glucose tolerance test among others. Compared with non-diabetic control mice, db/db+PBS mice exhibited decreased abundance of Ruminococaceae, Porphyromonadaceae and increased abundance of Rikenellaceae and Lactobacillaceae. FMT treatment reversed this effect on the microbiome. Eleven metabolites were changed between the db/db+PBS and db/db+FMT groups. Correlation analysis showed that the structural changes of the GM were correlated with host metabolite levels. We further showed that FMT treatment of db/db mice improved intestinal barrier function, reduced inflammation and caused an alteration in the number of circulating immune cells. FMT-mediated changes in the GM, serum metabolites, intestinal epithelial barrier, inflammation and circulating immune cells play an important role in the efficacy of FMT on T2DM disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The Feasibility of Incorporating a 3D Velocity Model Into Earthquake Location Around Salt Lake City, UT Using a Physics Informed Neural Network

Earthquake location algorithms typically require travel time calculation. Doing this calculation in 3D, despite advances in algorithm efficiency and computational power, can still be prohibitively expensive in terms of resources and storage. Implementation of high-resolution 3D models in routine earthquake location would be a significant step forward in most of the world. Machine learning algorithms have potential to act as substitutes for travel time calculation algorithms or stored travel time tables. We investigate EikoNet - a physics informed neural network machine learning model that estimates travel times very quickly and comes with negligible memory-overhead. Specifically, we apply EikoNet to the Wasatch Fault Community Velocity Model (WFCVM), a highly detailed and complex 3D velocity model of the Salt Lake City, UT region. While routine locations in the area and studies of the 2020 Magna, UT earthquake sequence used a 1D velocity model, a 3D model may help better our understanding the structure of the major fault in the region. Our primary goal was to test the speed, memory requirements, and accuracy of EikoNet compared to a reference eikonal solver. We find that while the EikoNet is exceedingly fast and requires little memory overhead, achieving acceptable accuracy in estimated travel times is difficult and requires extensive computational resources.

58 GEOSCIENCES↗
DOE OSTI2023

Case report: Fatal Legionella infection diagnosed via by metagenomic next-generation sequencing in a patient with chronic myeloid leukemia

Legionella is an aerobic, gram-negative, intracellular pathogen and is an important cause of community-acquired pneumonia. Legionella pneumophila is the most common causative agent of Legionella pneumonia. Clinical diagnosis of Legionella pneumonia is challenging due to the lack of specific clinical manifestations and the low positive rates of conventional pathogen detection methods. In this study, we report a case of a patient with chronic myeloid leukemia who developed rigors and high fever after chemotherapy and immunotherapy. Chest computed tomography revealed consolidation in the left lower lobe of the lung and ground-glass opacities in both lower lobes. Multiple blood cultures showed Escherichia coli , Staphylococcus aureus , Bacillus licheniformis , and positive results in the β-D-glucan test (G test). The patient was treated with various sensitive antimicrobial agents, including meropenem plus fluconazole, meropenem plus carpofungin, and vancomycin. Unfortunately, the patient’s condition gradually worsened and eventually resulted in death. On the following day of death, metagenomic next-generation sequencing (mNGS) of 1whole blood revealed L. pneumophila pneumonia with concurrent bloodstream infection (blood mNGS reads 114,302). These findings suggest that when conventional empirical antimicrobial therapy proves ineffective for critically ill patients with pneumonia, the possibility of combined Legionella infection must be considered, and mNGS can provide a diagnostic tool in such cases.

Bu, Chunhong↗
DOE OSTI2023

Enhancing alphafold-multimer-based protein complex structure prediction with MULTICOM in CASP15

To enhance the AlphaFold-Multimer-based protein complex structure prediction, we developed a quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine its outputs. MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural predictions by using both traditional sequence alignments and Foldseek-based structure alignments, ranks structural predictions through multiple complementary metrics, and refines the structural predictions via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. MULTICOM_qa ranked 3 rd among 26 CASP15 server predictors and MULTICOM_human ranked 7 th among 87 CASP15 server and human predictors. The average TM-score of the first predictions submitted by MULTICOM_qa for CASP15 assembly targets is ~0.76, 5.3% higher than ~0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 predictions submitted by MULTICOM_qa is ~0.80, about 8% higher than ~0.74 of the standard AlphaFold-Multimer. Moreover, the Foldseek Structure Alignment-based Multimer structure Generation (FSAMG) method outperforms the widely used sequence alignment-based multimer structure generation.

59 BASIC BIOLOGICAL SCIENCES↗