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At least 307 records · Page 17

Longitudinal changes in red blood cell distribution width decades after radiation exposure in atomic–bomb survivors

Red blood cell distribution width (RDW), which generally increases with age, is a risk marker for morbidity and mortality in various diseases. We investigated the association between elevated RDW and prior radiation exposure by examining longitudinal RDW changes in 4204 atomic-bomb survivors over 15 years. A positive association was found between RDW and radiation dose, wherein RDW increased by 0·18%/Gy. This radiation-associated effect increased as the participants aged. Elevated RDW was also associated with higher all-cause mortality. The biological mechanisms underlying these observed associations merit further investigation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Survival, growth and tag retention of juvenile European eel ( Anguilla anguilla L.) with implanted 12 mm passive integrated transponder tags and acoustic tags

To evaluate the efficiency of tagging juvenile European eels with implanted 12 mm passive integrated transponder (PIT) tags or Eel/Lamprey acoustic transmitters (ELATs), the authors studied tag retention, survival and growth of eels (7–25 g). Experimental eels were obtained from an eel farm, tagged and then released in a series of shallow dug-out ponds with a surface area of c. 200 m 2 . Tagged and control eels were distributed evenly, with 50 tagged and 50 control eels in each of four ponds, giving a total of 200 tagged and 200 control eels mixed. After 76 days, the ponds were drained, and eels were sampled and measured. A total of 344 eels (86%) were recaptured, indicating high survival. Tag retention was 99% as only one of the recaptured PIT-tagged eels had lost the tag and none of the ELAT tagged. The results demonstrated that tagging juvenile eels >16 cm with these small tags is indeed feasible. The growth of tagged and control fish was differentiated but generally low in length and negative in mass but did not differ between the three groups.

54 ENVIRONMENTAL SCIENCES↗

Tobacco-specific nitrosamine 1-(N-methyl-N-nitrosamino)-1-(3-pyridinyl)-4-butanal (NNA) causes DNA damage and impaired replication/transcription in human lung cells

Thirdhand smoke (THS) is a newly described health hazard composed of toxicants, mutagens and carcinogens, including nicotine-derived tobacco specific nitrosamines (TSNAs), one of which is 1-(N-methyl-N-nitrosamino)-1-(3-pyridinyl)-4-butanal (NNA). Although TSNAs are generally potent carcinogens, the risk of NNA, which is specific to THS, is poorly understood. We recently reported that THS exposure-induced adverse impact on DNA replication and transcription with implications in the development of cancer and other diseases. Here, we investigated the role of NNA in THS exposure-induced harmful effects on fundamental cellular processes. We exposed cultured human lung epithelial BEAS-2B cells to NNA. The formation of DNA base damages was assessed by Long Amplicon QPCR (LA-QPCR); DNA double-strand breaks (DSBs) and NNA effects on replication and transcription by immunofluorescence (IF); and genomic instability by micronuclei (MN) formation. We found increased accumulation of oxidative DNA damage and DSBs as well as activation of DNA damage response pathway, after exposure of cells to NNA. Impaired S phase progression was also evident. Consistent with these results, we found increased MN formation, a marker of genomic instability, in NNA-exposed cells. Furthermore, ongoing RNA synthesis was significantly reduced by NNA exposure, however, RNA synthesis resumed fully after a 24h recovery period only in wild-type cells but not in those deficient in transcription-coupled nucleotide excision repair (TC-NER). Importantly, these cellular effects are common with the THS-exposure induced effects. Our findings suggest that NNA in THS could be a contributing factor for THS exposure-induced adverse health effect.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring the Interaction of Amphiphilic Mycobacterial Lipoarabinomannan with Lipoproteins: Implications for Blood Based Diagnosis

Currently, over one-third of the global population is infected with tuberculosis (TB), one of the world’s most deadly infectious diseases. The current gold standard for TB diagnosis is microbiological culture, which can take up to 6-8 weeks, which is not conducive to timely treatment. There are no reliable diagnostics for TB. Disease manifestation and outcome of diagnostic tests for TB is influenced by co-morbidities such as HIV co-infection, further complicating diagnostics development. Thus, there is a need for reliable diagnostics for TB. This is especially true in pediatric populations where the differential disease presentation further complicates outcomes. This dissertation describes the development and evaluation of new tailored methods-lipoprotein capture and membrane insertion- for the discriminative detection of an amphiphilic mycobacterial biomarker, lipoarabinomannan (LAM), for diagnosis of TB in adult and pediatric populations. LAM is released by Mycobacterium tuberculosis during active infection and associates with serum lipoproteins such as high and low density lipoproteins (HDL/LDL) in the human host. The guiding hypothesis of this work is that the vi sequestration of LAM in immune complexes and by lipoprotein carriers in the host contributes to difficulty in detection of the amphiphilic antigen in blood. To this end, we have evaluated the use of tailored amphiphile detection assays to process and measure sequestered LAM in host blood, and examined the application of this methodology in adults and children with TB disease. In addition, we have developed and studied an in vitro cell model to further extrapolate the impact of association of LAM with host carriers on its ability to induce innate immune processes, in order to better refine and design strategies for its direct detection. Overall, our conclusions indicate that the amphiphilic biochemistry of LAM and its interaction with lipoproteins is a feature which should be taken into account for the effective development of diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗

Mastering Medaka Culture: Improved Techniques for Increasing Egg and Fry Production in Japanese Rice Fish ( Oryzias latipes )

Aquatic systems are integral to ecosystem function and human health. By trapping sediments and retaining nutrients, wetlands protect our water quality. However, a wetland’s capacity to trap sediments and nutrients also means they can capture many contaminants (e.g., heavy metals and radionuclides) released into the environment due to anthropogenic activities. Both heavy metals and radionuclides have detrimental effects on wildlife at acute dosages. However, little is known regarding underlying biological responses associated with chronic low dose exposure to both ionizing radiation and heavy metals. Our long-term research goal is to work to fill this knowledge gap using Medaka (Oryzias latipes), small fish amenable to experimental manipulation. However, the current study focused on altering the husbandry protocol of a laboratory colony of Medaka in a way that would increase colony size to at least 400 individual fish over a six-week period. At the beginning of our work, we followed a strict cleaning, feeding and egg harvesting protocol. Two weeks into our work, we suspected that food limitations may be negatively impacting egg production and noticed fungal growth on eggs. Thus, we altered the feeding regime and egg harvesting protocol. The altered protocol more than tripled egg production and almost doubled of fry production. By the end of our study the colony had 673 individuals: 191 adults and 482 fry. Furthermore, our protocol changes resulted in growth of the colony at sufficient numbers to begin experiments related to investigating sub-lethal impacts of heavy metals and radionuclides on Medaka.

Thompson, Melissa↗

Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization

Abstract Background Microbiome studies have uncovered associations between microbes and human, animal, and plant health outcomes. This has led to an interest in developing microbial interventions for treatment of disease and optimization of crop yields which requires identification of microbiome features that impact the outcome in the population of interest. That task is challenging because of the high dimensionality of microbiome data and the confounding that results from the complex and dynamic interactions among host, environment, and microbiome. In the presence of such confounding, variable selection and estimation procedures may have unsatisfactory performance in identifying microbial features with an effect on the outcome. Results In this manuscript, we aim to estimate population-level effects of individual microbiome features while controlling for confounding by a categorical variable. Due to the high dimensionality and confounding-induced correlation between features, we propose feature screening, selection, and estimation conditional on each stratum of the confounder followed by a standardization approach to estimation of population-level effects of individual features. Comprehensive simulation studies demonstrate the advantages of our approach in recovering relevant features. Utilizing a potential-outcomes framework, we outline assumptions required to ascribe causal, rather than associational, interpretations to the identified microbiome effects. We conducted an agricultural study of the rhizosphere microbiome of sorghum in which nitrogen fertilizer application is a confounding variable. In this study, the proposed approach identified microbial taxa that are consistent with biological understanding of potential plant-microbe interactions. Conclusions Standardization enables more accurate identification of individual microbiome features with an effect on the outcome of interest compared to other variable selection and estimation procedures when there is confounding by a categorical variable.

59 BASIC BIOLOGICAL SCIENCES↗

Knowledge graph-aided Bayesian active learning for top- K genetic interaction discovery

In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the development of these predictive algorithms for mammalian systems has been hampered by limited datasets and high experimental costs. In this study, we present a Bayesian active learning framework designed to discover pairwise host gene knockdowns that effectively inhibit viral proliferation in an in vitro HIV-1 infection model. Our method leverages a biological knowledge graph as side information and employs a computationally efficient batch diversification approach. We evaluated this framework using a dataset of viral load measurements obtained from multi-day dual-gene depletion experiments, encompassing all possible pairwise knockdowns of over 350 host genes associated with HIV infection. We demonstrate that our framework rapidly identifies the most effective gene knockdown pairs for reducing viral load. Furthermore, we show that incorporating side information enhances performance during the early stages of active learning (low data regime), while our batch diversification strategy significantly boosts performance in later stages (high data regime). This framework is general and can be adapted to explore gene interactions in other contexts, such as synthetic lethality prediction and mapping epistatic effects across quantitative trait loci.

Computational biology and bioinformatics↗

Critical steps in preventing future pandemics. Early lessons from the Covid-19 crisis for addressing natural and deliberate biological threats.

This report summarizes a virtual workshop on early lessons from the COVID-19 pandemic as they pertain to proactively addressing future biological threats. Co-hosted by Sandia National Laboratory (Sandia) and the Council on Strategic Risks (CSR) in August 2020, the discussion involved experts who at that time were leading innovative efforts in various U.S. government agencies, industry, and academia sharing observations from their ongoing pandemic response efforts. Based on the input by these expert participants, it is clear that even though the pandemic response is ongoing, the following recommendations will be important to consider for more successfully addressing biological threats in the future: Continue building on the cross-sector collaboration and agility shown in the COVID-19 response; Expand capabilities for detecting biological threats early; Prioritize ways to create and disseminate medical countermeasures even faster; Create the U.S. bio industrial base needed for rapid response to biological threats, and keep it healthy; and, Major government reorganization may not be needed if there is effective work to form coalitions, improve coordination, and expand steady-state and surge capacities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimized simple and affordable procedure for differentiation of monocyte-derived dendritic cells from LRF: An accessible and valid alternative biological source

Dendritic cells are one of the most popular immune cells, which plays a remarkable role in both immunotherapy and tolerance induction. Due to unwanted side effects of leukocyte presence in donated blood, the policy of blood service is the pre-storage reduction of leukocytes, which today, filtration is the most common method for this purpose. The filtration method has led to diminished access to Buffy coat as a generally used conventional source of biological cells. We developed a simple, affordable, and reproducible method for dendritic cell differentiation from filter-derived monocytes and, the results of the filter study were compared with differentiated DCs from the conventional buffy coat-derived monocytes. The Monocytes were recovered from leukoreduction filter using an optimized protocol with supplemented PBS buffer. Following the adhesion method, CD14{sup +} Monocyte-enriched population with the purity of 94 % was obtained. After cytokine stimulation over a 6-day period and maturation induction by LPS, differentiated DCs were evaluated for morphology, surface markers (CD86, CD40, CD83 and, HLA-DR), antigen uptake potency and IL-12 secretion. Analysis and comparison of the results represented no significant difference between the two groups. Accordingly, we conclude that leukoreduction filters could be introduced as a reliable and research-grade source of monocyte for DC generation in biological research.

60 APPLIED LIFE SCIENCES↗

OSCA1 is an osmotic specific sensor: a method to distinguish Ca 2+ -mediated osmotic and ionic perception

Genetic mutants defective in stimulus-induced Ca 2+ increases have been gradually isolated, allowing the identification of cell-surface sensors/receptors, such as the osmosensor OSCA1. However, determining the Ca 2+ -signaling specificity to various stimuli in these mutants remains a challenge. For instance, less is known about the exact selectivity between osmotic and ionic stresses in the osca1 mutant. Here, we have developed a method to distinguish the osmotic and ionic effects by analyzing Ca 2+ increases, and demonstrated that osca1 is impaired primarily in Ca 2+ increases induced by the osmotic but not ionic stress. We recorded Ca 2+ increases induced by sorbitol (osmotic effect, OE) and NaCl/CaCl 2 (OE + ionic effect, IE) in Arabidopsis wild-type and osca1 seedlings. Here we assumed the NaCl/CaCl 2 total effect (TE) = OE + IE, then developed procedures for Ca 2+ imaging, image analysis and mathematic fitting/modeling, and found osca1 defects mainly in OE. The osmotic specificity of osca1 suggests that osmotic and ionic perceptions are independent. The precise estimation of these two stress effects is applicable not only to new Ca 2+ -signaling mutants with distinct stimulus specificity but also the complex Ca 2+ signaling crosstalk among multiple concurrent stresses that occur naturally, and will enable us to specifically fine tune multiple signal pathways to improve crop yields.

Arabidopsis↗

Renewable energy and biological conservation in a changing world

Without a shift to renewable energy sources, climate change will have adverse effects on many terrestrial and aquatic species. On the other hand, replacing fossil fuels with renewable energy will have different effects on wildlife, some negative. To protect biota, while navigating the complexities surrounding the transition to renewable energy, will require sharing knowledge between energy experts and wildlife experts, as well as policy makers and resource managers. This special issue is intended to advance the conversation. Interactions between renewable energy facilities and fauna are complex. Each source of renewable energy has its own conservation concerns, and each presents its own set of opportunities for mitigation; Other concerns and mitigations are shared. In this overview, we review climate risks to biota, clarify the complementarities among renewables for the conservation community, and summarize research on energy effects on biota for the energy community. The papers invited for this special issue address fossil (coal, oil, natural gas) and renewable energy (terrestrial biomass energy, hydropower, marine-hydrokinetic energy, wind energy, solar energy) and affected fauna. Finally, we hope that the results of these studies, and others like them, set us on a path toward low-carbon energy systems that provide society with energy while protecting future biodiversity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Correlating Protein Dynamics and Catalytic Activity of a Model Hydrogenase Using Paramagnetic and Biological Nuclear Magnetic Resonance Spectroscopy

Rational catalyst design remains a significant challenge, with electronic structure, steric, and electrostatic effects known to contribute to activity. Recently, dynamics has been recognized as another factor that impacts catalysis, though identifying and predicting these effects has remained out of reach. Nickel-substituted rubredoxin (NiRd), a protein-based mimic of a hydrogenase enzyme, serves as a model catalytic system in which dynamics can be systematically investigated with respect to activity. While over 30 secondary-sphere mutants of NiRd have been shown to be catalytically active, no significant correlation was observed between the rates and catalytic overpotential or electronic structure, prompting questions about the protein-derived factors that modulate activity. Here, in this work, NMR spectroscopy was used to investigate the roles of substrate accessibility, protein dynamics, and protein stability in controlling catalysis. Significant paramagnetic effects from the nickel center (S = 1) isolate the methylene proton resonances of the metal-coordinating cysteine residues. The sensitivity of resonance positions and linewidths to local environment offers an opportunity to study dynamical molecular changes around the metal center with high resolution. Machine learning algorithms were employed to identify correlations between the catalytic activity and the paramagnetic NMR spectra. These analyses revealed spectroscopic features of specific cysteine protons that report on catalytic overpotential and increased turnover rates, which are further supported by the results obtained using high-field NMR techniques. Collectively, these studies indicate the potential for multifrequency NMR techniques to resolve key contributors to catalytic activity and highlight the importance of local and outer-sphere dynamics.

Protein Engineering↗

The Importance of Sharing Data in Systems Biology

Systems biology research spans a range of biological scales and science domains, and often requires a collaborative effort to collect and share data so that integration is possible. However, sharing data effectively is a challenging task that requires effort and alignment between collaborative partners, as well as coordination between organizations, repositories, and journals. As a community of systems biology researchers, we must get better at efficiently sharing data, and ensuring that shared data comes with the recognition and citations it deserves.

Wood-Charlson, Elisha M. (ORCID:0000000195577715)↗

Comparative Dissolution of Iron-Bearing Minerals by Catecholate and Hydroxamate Siderophores under Oxic and Anoxic Conditions

Siderophores play a crucial role in biological iron (Fe) acquisition and mobilization by promoting Fe mineral and rock weathering. While the effects of the hydroxamate siderophore desferrioxamine B (DFOB) have been extensively studied, the role of catecholates in the dissolution of Fe mineral and rock under varying redox conditions remain limited. Moreover, despite Fe being one of the most redox-active metals, the siderophore-mediated redox transformations of solid-phase Fe and their impact on mineral dissolution are not well understood. Herein, this study systematically investigated dissolution behavior of both Fe(II) and Fe(III)-bearing minerals and rocks (Fe(II)- bearing basalt and olivine, and Fe(III)- bearing nontronite and goethite), by two structurally distinct biological siderophores, catecholate protochelin and hydroxamate DFOB, under both oxic and anoxic conditions. Batch experiments quantified Fe and transition metals (Mn, Ni, Zn, Mo) released from the tested minerals in the presence of siderophores. Throughout the dissolution experiments, siderophore concentrations and Fe-siderophore complexation in solutions were measured using UV-vis spectrometry. Fe redox changes under oxic and anoxic conditions by siderophores were determined, and mineral surface alterations following siderophore treatments were characterized through scanning electron microscopy (SEM) and time-of-flight secondary ion mass spectroscopy (ToF-SIMS). Results revealed distinct interplays of dissolution mechanisms, including ligand-exchange promoted dissolution and reductive dissolution, along with Fe(III) reduction and Fe(II) oxidation, contributing to the Fe(II)- and Fe(III)-rich mineral weathering under varying redox conditions. Under oxic conditions, both protochelin and DFOB enhanced Fe release from Fe(II)-rich basalt and olivine more effectively than from Fe(III)-rich minerals. DFOB induced greater Fe(II)-mineral dissolution than protochelin. This difference was attributed to a higher level of Fe(II) oxidation by DFOB in contrast to protochelin, as well as the protochelin oxidation with the loss of Fe binding groups (catechols). Under anoxic conditions, both siderophores significantly reduced Fe(III) in nontronite and goethite, with protochelin demonstrating substantially stronger Fe(III) reduction capacity than DFOB. However, Fe(III) reduction negatively impacted Fe release from Fe(III)-rich minerals. Instead, Fe release from Fe(II)-rich minerals was enhanced under anoxic conditions due to the absence of Fe(II) oxidation and labile Fe(II). Variations in siderophore adsorption also contributed to dissolution differences. Beyond iron, the release of transition metals from tested minerals was influenced by elemental contents, mineral compositions, and siderophore types, revealing distinct metal- and siderophore-dependent patterns. This systematic investigation highlights the roles of siderophores in Fe redox cycling and metal mobilization, enhancing our understanding of different siderophore behaviors in siderophore-mediated microbial metal acquisition within redox-dynamic environments, with implications for bioleaching industries and applications in agriculture and climate change mitigation.

Guo, Dongyi↗

Isoflavone supplementation, via red clover hay, alters the rumen microbial community and promotes weight gain of steers grazing mixed grass pastures

Biochanin A, an isoflavone present in the pasture legume red clover (Trifloium pratense L.), alters fermentation in the rumen of cattle and other ruminants. Biochanin A inhibits hyperammonia-producing bacteria and promotes cellulolytic bacteria and fiber catalysis in vitro and ex vivo. Consequently, biochanin A supplementation improves weight gain in grazing steers. Red clover contains biologically active isoflavones that may act synergistically. Therefore, the objective was to evaluate the effect of two levels of red clover hay on growth performance and the microbial community in growing steers grazing mixed grass pastures. A grazing experiment was conducted over 2 early growing seasons (2016 and 2017) with 36 cross-bred steers and twelve rumen-fistulated, growing Holstein steers for evaluation of average daily gain and rumen microbiota, respectively. Steers were blocked by body weight and assigned to pastures with one of four treatments: 1) pasture only, 2) pasture + dry distillers’ grains (DDG), 3) pasture + DDG + low level of red clover hay (~15% red clover diet), or 4) pasture + DDG + high level of red clover hay (~30% red clover diet). DDG were added to treatments to meet protein requirements and to balance total protein supplementation between treatments. All supplementation strategies (DDG ± red clover hay) increased average daily gains in comparison to pasture-only controls (P < 0.05), with a low level of red clover supplementation being the most effective (+0.17 kg d-1 > DDG only controls; P < 0.05). Similarly, hyper-ammonia-producing bacteria inhibition (10–100-fold; P < 0.05), fiber catalysis (+10–25%; P < 0.05) and short chain fatty acid concentrations were greatest with the low red clover supplement (+~25%; P < 0.05). These results provide evidence that lower levels or red clover supplementation may be optimal for maximizing overall microbial community function and animal performance in grazing steers.

54 ENVIRONMENTAL SCIENCES↗

In vivo Functional Characterization of Hydrophilic X2 Modules in the Cellulosomal Scaffolding Protein

As part of free cellulases or scaffolding proteins in cellulosomes, the hydrophilic non-catalytic X2 module is widely distributed in cellulolytic Clostridia or other Firmicutes bacteria. Previous biochemical studies suggest that X2 modules might increase the solubility and substrate binding affinity of X2-bearing proteins. However, their in vivo biological functions remain elusive. Here we employed CRISPR-Cas9 editing to genetically modify X2 modules by deleting the conserved motif (NGNT) from the CipC scaffoldin. Both single and double X2 mutants (X2-N: near the N terminus of CipC; X2-C: near the C terminus of CipC) presented similar stoichiometric compositions in isolated cellulosomes as the wildtype strain (WT). These X2 mutants had an elongated adaptation stage during growth on cellulose compared to cellobiose. Compared to WT, the double mutant ΔX2-NC reduced cellulose degradation by 15% and the amount of released soluble sugars by 63%. Since single X2 mutants did not present such obvious physiological changes as ΔX2-NC, there seems to be a functional redundancy between X2 modules in CipC. The in vivo adhesion assay revealed that ΔX2-NC decreased cell attachment to cellulose by 70% but a weaker effect was also overserved in single X2 mutants. These results highlight the in vivo biological role of X2 in increasing cellulose degradation efficiency by enhancing the binding affinity between cells and cellulose, which provides new perspectives for microbial engineering.

59 BASIC BIOLOGICAL SCIENCES↗

mTOR regulates aerobic glycolysis through NEAT1 and nuclear paraspeckle-mediated mechanism in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is a major form of liver cancer and a leading cause of cancer-related death worldwide. New insights into HCC pathobiology and mechanism of drug actions are urgently needed to improve patient outcomes. HCC undergoes metabolic reprogramming of glucose metabolism from respiration to aerobic glycolysis, a phenomenon known as the ‘Warburg Effect’ that supports rapid cancer cell growth, survival, and invasion. mTOR is known to promote Warburg Effect, but the underlying mechanism(s) remains poorly defined. The aim of this study is to understand the mechanism(s) and significance of mTOR regulation of aerobic glycolysis in HCC. We profiled mTORC1-dependent long non-coding RNAs (lncRNAs) by RNA-seq of HCC cells treated with rapamycin. Chromatin immunoprecipitation (ChIP) and luciferase reporter assays were used to explore the transcriptional regulation of NEAT1 by mTORC1. [U- 13 C]-glucose labeling and metabolomic analysis, extracellular acidification Rate (ECAR) by Seahorse XF Analyzer, and glucose uptake assay were used to investigate the role of mTOR-NEAT1-NONO signaling in the regulation of aerobic glycolysis. RNA immunoprecipitation (RIP) and NONO-binding motif scanning were performed to identify the regulatory mechanism of pre-mRNA splicing by mTOR-NEAT1. Myristoylated AKT1 (mAKT1)/NRASV 12 -driven HCC model developed by hydrodynamic transfection (HDT) was employed to explore the significance of mTOR-NEAT1 signaling in HCC tumorigenesis and mTOR-targeted therapy. mTOR regulates lncRNA transcriptome in HCC and that NEAT1 is a major mTOR transcriptional target. Interestingly, although both NEAT1_1 and NEAT1_2 are down-regulated in HCC, only NEAT1_2 is significantly correlated with poor overall survival of HCC patients. NEAT1_2 is the organizer of nuclear paraspeckles that sequester the RNA-binding proteins NONO and SFPQ. We show that upon oncogenic activation, mTORC1 suppresses NEAT1_2 expression and paraspeckle biogenesis, liberating NONO/SFPQ, which in turn, binds to U5 within the spliceosome, stimulating mRNA splicing and expression of key glycolytic enzymes. This series of actions lead to enhanced glucose transport, aerobic glycolytic flux, lactate production, and HCC growth both in vitro and in vivo. Furthermore, the paraspeckle-mediated mechanism is important for the anticancer action of US FDA-approved drugs rapamycin/temsirolimus. These findings reveal a molecular mechanism by which mTOR promotes the ‘Warburg Effect’, which is important for the metabolism and development of HCC, and anticancer response of mTOR-targeted therapy.

59 BASIC BIOLOGICAL SCIENCES↗

Learning emergent partial differential equations in a learned emergent space

We propose an approach to learn effective evolution equations for large systems of interacting agents. This is demonstrated on two examples, a well-studied system of coupled normal form oscillators and a biologically motivated example of coupled Hodgkin-Huxley-like neurons. For such types of systems there is no obvious space coordinate in which to learn effective evolution laws in the form of partial differential equations. In our approach, we accomplish this by learning embedding coordinates from the time series data of the system using manifold learning as a first step. In these emergent coordinates, we then show how one can learn effective partial differential equations, using neural networks, that do not only reproduce the dynamics of the oscillator ensemble, but also capture the collective bifurcations when system parameters vary. The proposed approach thus integrates the automatic, data-driven extraction of emergent space coordinates parametrizing the agent dynamics, with machine-learning assisted identification of an emergent PDE description of the dynamics in this parametrization.

97 MATHEMATICS AND COMPUTING↗