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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Layer-by-layer disentanglement of Bloch states

Layer-by-layer material engineering has produced interesting quantum phenomena such as interfacial superconductivity and the quantum anomalous Hall effect. However, probing electronic states layer-by-layer remains challenging. This is exemplified by the difficulty in understanding the layer origins of topological electronic states in magnetic topological insulators. In this work, we report a layer-encoded frequency-domain photoemission experiment on the magnetic topological insulator (MnBi 2 Te 4 )(Bi 2 Te 3 ) that characterizes the origins of its electronic states. Infrared laser excitations launch coherent lattice vibrations with the layer index encoded by the vibration frequency. Photoemission spectroscopy then tracks the electron dynamics, where the layer information is carried in the frequency domain. This layer-frequency correspondence reveals wavefunction relocation of the topological surface state from the top magnetic layer into the buried second layer, reconciling the controversy over the vanishing broken-symmetry energy gap in (MnBi 2 Te 4 )(Bi 2 Te 3 ) and its related compounds. The layer-frequency correspondence can be harnessed to disentangle electronic states layer-by-layer in a broad class of van der Waals superlattices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An atlas of dynamic chromatin landscapes in mouse fetal development

The Encyclopedia of DNA Elements (ENCODE) project has established a genomic resource for mammalian development, profiling a diverse panel of mouse tissues at 8 developmental stages from 10.5 days after conception until birth, including transcriptomes, methylomes and chromatin states. Here we systematically examined the state and accessibility of chromatin in the developing mouse fetus. In total we performed 1,128 chromatin immunoprecipitation with sequencing (ChIP–seq) assays for histone modifications and 132 assay for transposase-accessible chromatin using sequencing (ATAC–seq) assays for chromatin accessibility across 72 distinct tissue-stages. We used integrative analysis to develop a unified set of chromatin state annotations, infer the identities of dynamic enhancers and key transcriptional regulators, and characterize the relationship between chromatin state and accessibility during developmental gene regulation. We also leveraged these data to link enhancers to putative target genes and demonstrate tissue-specific enrichments of sequence variants associated with disease in humans. The mouse ENCODE data sets provide a compendium of resources for biomedical researchers and achieve, to our knowledge, the most comprehensive view of chromatin dynamics during mammalian fetal development to date.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The changing mouse embryo transcriptome at whole tissue and single-cell resolution

During mammalian embryogenesis, differential gene expression gradually builds the identity and complexity of each tissue and organ system 1 . Here we systematically quantified mouse polyA-RNA from day 10.5 of embryonic development to birth, sampling 17 tissues and organs. The resulting developmental transcriptome is globally structured by dynamic cytodifferentiation, body-axis and cell-proliferation gene sets that were further characterized by the transcription factor motif codes of their promoters. We decomposed the tissue-level transcriptome using single-cell RNA-seq (sequencing of RNA reverse transcribed into cDNA) and found that neurogenesis and haematopoiesis dominate at both the gene and cellular levels, jointly accounting for one-third of differential gene expression and more than 40% of identified cell types. By integrating promoter sequence motifs with companion ENCODE epigenomic profiles, we identified a prominent promoter de-repression mechanism in neuronal expression clusters that was attributable to known and novel repressors. Focusing on the developing limb, single-cell RNA data identified 25 candidate cell types that included progenitor and differentiating states with computationally inferred lineage relationships. We extracted cell-type transcription factor networks and complementary sets of candidate enhancer elements by using single-cell RNA-seq to decompose integrative cis -element (IDEAS) models that were derived from whole-tissue epigenome chromatin data. These ENCODE reference data, computed network components and IDEAS chromatin segmentations are companion resources to the matching epigenomic developmental matrix, and are available for researchers to further mine and integrate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Borgs are giant genetic elements with potential to expand metabolic capacity

Anaerobic methane oxidation exerts a key control on greenhouse gas emissions1, yet factors that modulate the activity of microorganisms performing this function remain poorly understood. Here we discovered extraordinarily large, diverse DNA sequences that primarily encode hypothetical proteins through studying groundwater, sediments and wetland soil where methane production and oxidation occur. Four curated, complete genomes are linear, up to approximately 1 Mb in length and share genome organization, including replichore structure, long inverted terminal repeats and genome-wide unique perfect tandem direct repeats that are intergenic or generate amino acid repeats. We infer that these are highly divergent archaeal extrachromosomal elements with a distinct evolutionary origin. Gene sequence similarity, phylogeny and local divergence of sequence composition indicate that many of their genes were assimilated from methane-oxidizing Methanoperedens archaea. We refer to these elements as ‘Borgs’. We identified at least 19 different Borg types coexisting with Methanoperedens spp. in four distinct ecosystems. Borgs provide methane-oxidizing Methanoperedens archaea access to genes encoding proteins involved in redox reactions and energy conservation (for example, clusters of multihaem cytochromes and methyl coenzyme M reductase). These data suggest that Borgs might have previously unrecognized roles in the metabolism of this group of archaea, which are known to modulate greenhouse gas emissions, but further studies are now needed to establish their functional relevance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural basis of Gabija anti-phage defence and viral immune evasion

Bacteria encode hundreds of diverse defence systems that protect them from viral infection and inhibit phage propagation. Gabija is one of the most prevalent anti-phage defence systems, occurring in more than 15% of all sequenced bacterial and archaeal genomes, but the molecular basis of how Gabija defends cells from viral infection remains poorly understood. Here we use X-ray crystallography and cryo-electron microscopy (cryo-EM) to define how Gabija proteins assemble into a supramolecular complex of around 500 kDa that degrades phage DNA. Gabija protein A (GajA) is a DNA endonuclease that tetramerizes to form the core of the anti-phage defence complex. Two sets of Gabija protein B (GajB) dimers dock at opposite sides of the complex and create a 4:4 GajA–GajB assembly (hereafter, GajAB) that is essential for phage resistance in vivo. We show that a phage-encoded protein, Gabija anti-defence 1 (Gad1), directly binds to the Gabija GajAB complex and inactivates defence. A cryo-EM structure of the virally inhibited state shows that Gad1 forms an octameric web that encases the GajAB complex and inhibits DNA recognition and cleavage. Our results reveal the structural basis of assembly of the Gabija anti-phage defence complex and define a unique mechanism of viral immune evasion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Birth of protein folds and functions in the virome

The rapid evolution of viruses generates proteins that are essential for infectivity and replication but with unknown functions, due to extreme sequence divergence. Here, using a database of 67,715 newly predicted protein structures from 4,463 eukaryotic viral species, we found that 62% of viral proteins are structurally distinct and lack homologues in the AlphaFold database. Among the remaining 38% of viral proteins, many have non-viral structural analogues that revealed surprising similarities between human pathogens and their eukaryotic hosts. Structural comparisons suggested putative functions for up to 25% of unannotated viral proteins, including those with roles in the evasion of innate immunity. In particular, RNA ligase T-like phosphodiesterases were found to resemble phage-encoded proteins that hydrolyse the host immune-activating cyclic dinucleotides 3',3'- and 2',3'-cyclic GMP-AMP (cGAMP). Experimental analysis showed that RNA ligase T homologues encoded by avian poxviruses similarly hydrolyse cGAMP, showing that RNA ligase T-mediated targeting of cGAMP is an evolutionarily conserved mechanism of immune evasion that is present in both bacteriophage and eukaryotic viruses. Together, the viral protein structural database and analyses presented here afford new opportunities to identify mechanisms of virus–host interactions that are common across the virome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Enzalutamide response in a panel of prostate cancer cell lines reveals a role for glucocorticoid receptor in enzalutamide resistant disease

Representative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3 , the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC ) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1 . Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An adaptive approach to machine learning for compact particle accelerators

Abstract Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However, for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no longer accurately represented by the data with which the ML models were trained. For complex systems, re-training is only possible if the changes are slow relative to the rate at which large numbers of new input-output training data can be non-invasively recorded. In this work, we present an approach to deep learning for time-varying systems that does not require re-training, but uses instead an adaptive feedback in the architecture of deep convolutional neural networks (CNN). The feedback is based only on available system output measurements and is applied in the encoded low-dimensional dense layers of the encoder-decoder CNNs. First, we develop an inverse model of a complex accelerator system to map output beam measurements to input beam distributions, while both the accelerator components and the unknown input beam distribution vary rapidly with time. We then demonstrate our method on experimental measurements of the input and output beam distributions of the HiRES ultra-fast electron diffraction (UED) beam line at Lawrence Berkeley National Laboratory, and showcase its ability for automatic tracking of the time varying photocathode quantum efficiency map. Our method can be successfully used to aid both physics and ML-based surrogate online models to provide non-invasive beam diagnostics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Knockout of ABC transporter gene ABCA2 confers resistance to Bt toxin Cry2Ab in Helicoverpa zea

Evolution of pest resistance reduces the benefits of widely cultivated genetically engineered crops that produce insecticidal proteins derived from Bacillus thuringiensis (Bt). Better understanding of the genetic basis of pest resistance to Bt crops is needed to monitor, manage, and counter resistance. Previous work shows that in several lepidopterans, resistance to Bt toxin Cry2Ab is associated with mutations in the gene encoding the ATP-binding cassette protein ABCA2. The results here show that mutations introduced by CRISPR/Cas9 gene editing in the Helicoverpa zea (corn earworm or bollworm) gene encoding ABCA2 (HzABCA2) can cause resistance to Cry2Ab. Disruptive mutations in HzABCA2 facilitated the creation of two Cry2Ab-resistant strains. A multiple concentration bioassay with one of these strains revealed it had > 200-fold resistance to Cry2Ab relative to its parental susceptible strain. All Cry2Ab-resistant individuals tested had disruptive mutations in HzABCA2. We identified five disruptive mutations in HzABCA2 gDNA. The most common mutation was a 4-bp deletion in the expected Cas9 guide RNA target site. The results here indicate that HzABCA2 is a leading candidate for monitoring Cry2Ab resistance in field populations of H. zea.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Genotypic analyses of IncHI2 plasmids from enteric bacteria

Incompatibility (Inc) HI2 plasmids are large (typically > 200 kb), transmissible plasmids that encode antimicrobial resistance (AMR), heavy metal resistance (HMR) and disinfectants/biocide resistance (DBR). To better understand the distribution and diversity of resistance-encoding genes among IncHI2 plasmids, computational approaches were used to evaluate resistance and transfer-associated genes among the plasmids. Complete IncHI2 plasmid (N - 667) sequences were extracted from GenBank and analyzed using AMRFinderPlus, IntegronFinder and Plasmid Transfer Factor database. The most common IncHI2-carrying genera included Enterobacter (N = 209), Escherichia (N = 208), and Salmonella (N = 204). Resistance genes distribution was diverse, with plasmids from Escherichia and Salmonella showing general similarity in comparison to Enterobacter and other taxa, which grouped together. Plasmids from Enterobacter and other taxa had a higher prevalence of multiple mercury resistance genes and arsenic resistance gene, arsC, compared to Escherichia and Salmonella. For sulfonamide resistance, sul1 was more common among Enterobacter and other taxa, compared to sul2 and sul3 for Escherichia and Salmonella. Similar gene diversity trends were also observed for tetracyclines, quinolones, β-lactams, and colistin. Over 99% of plasmids carried at least 25 IncHI2-associated conjugal transfer genes. These findings highlight the diversity and dissemination potential for resistance across different enteric bacteria and value of computational-based approaches for the resistance-gene assessment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Direct genome-scale screening of Gluconobacter oxydans B58 for rare earth element bioleaching

Abstract The transition to a sustainable energy economy will require an enormous increase in the supply of rare earth elements (REEs). Bioleaching offers a promising alternative to conventional hydrometallurgical methods for REE extraction from low-grade ores. However, exploiting this potential remains challenging due to large gaps in our understanding of the genetics involved, and inadequate biological tools to address them. We generated a highly non-redundant whole-genome knockout collection for the bioleaching microbe Gluconobacter oxydans B58, reducing redundancy by 85% compared to the previous best collection. This new collection was directly screened for bioleaching neodymium from a synthetic monazite powder, identifying 89 genes important for bioleaching, 68 of which have not previously been associated with this mechanism. We conducted bench-scale experiments to validate the extraction efficiency of promising strains: 8 demonstrated significant increases in extraction by up to 111% (δ GO_1598 , disruption of the gene encoding the orotate phosphoribosyltransferase enzyme PyrE), and one strain significantly reduced it by 97% (δ GO_1096 , disruption of the gene encoding the GTP-binding protein TypA). Notable changes in pH were only observed for 3 strains, suggesting an important role for non-acid mechanisms in bioleaching. These findings provide valuable insights into further enhancing REE-bioleaching by G. oxydans through genetic engineering.

Marecos, Sabrina (ORCID:0000000158529933)↗
DOE OSTI2026

Simulating fermions with a digital quantum computer

Quantum computers are expected to become a powerful tool for studying physical quantum systems. Consequently, a number of quantum algorithms to determine the physical properties of such systems have been developed. Although qubit-based quantum computers are naturally suited to the study of spin-1/2 systems, systems containing other degrees of freedom must first be encoded into qubits. Transformations to and from fermionic degrees of freedom have long been an important tool in physics and chemistry, which is now finding another application in the simulation of fermionic systems on quantum computers based on qubits. In this work, we discuss methods for encoding fermionic degrees of freedom into qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

It is widely known that neural networks (NNs) are universal approximators of continuous functions. However, a less known but powerful result is that a NN with a single hidden layer can accurately approximate any nonlinear continuous operator. This universal approximation theorem of operators is suggestive of the structure and potential of deep neural networks (DNNs) in learning continuous operators or complex systems from streams of scattered data. Here, in this work, we thus extend this theorem to DNNs. We design a new network with small generalization error, the deep operator network (DeepONet), which consists of a DNN for encoding the discrete input function space (branch net) and another DNN for encoding the domain of the output functions (trunk net). We demonstrate that DeepONet can learn various explicit operators, such as integrals and fractional Laplacians, as well as implicit operators that represent deterministic and stochastic differential equations. We study different formulations of the input function space and its effect on the generalization error for 16 different diverse applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Experimental discovery of structure–property relationships in ferroelectric materials via active learning

Emergent functionalities of structural and topological defects in ferroelectric materials underpin an extremely broad spectrum of applications ranging from domain wall electronics to high dielectric and electromechanical responses. Many of these functionalities have been discovered and quantified via local scanning probe microscopy methods. However, the search has until now been based on either trial and error, or using auxiliary information such as the topography or domain wall structure to identify potential objects of interest on the basis of the intuition of operator or pre-existing hypotheses, with subsequent manual exploration. Here we report the development and implementation of a machine learning framework that actively discovers relationships between local domain structure and polarization-switching characteristics in ferroelectric materials encoded in the hysteresis loop. The hysteresis loops and their scalar descriptors such as nucleation bias, coercive bias and the hysteresis loop area (or more complex functionals of hysteresis loop shape) and corresponding uncertainties are used to guide the discovery of these relationships via automated piezoresponse force microscopy and spectroscopy experiments. As such, this approach combines the power of machine learning methods to learn the correlative relationships between high-dimensional data, as well as human-based physics insights encoded into the acquisition function. For ferroelectric materials, this automated workflow demonstrates that the discovery path and sampling points of on- and off-field hysteresis loops are largely different, indicating that on- and off-field hysteresis loops are dominated by different mechanisms. Here, the proposed approach is universal and can be applied to a broad range of modern imaging and spectroscopy methods ranging from other scanning probe microscopy modalities to electron microscopy and chemical imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Activity, structure, and diversity of Type II proline-rich antimicrobial peptides from insects

Abstract Apidaecin 1b (Api), the first characterized Type II Proline-rich antimicrobial peptide (PrAMP), is encoded in the honey bee genome. It inhibits bacterial growth by binding in the nascent peptide exit tunnel of the ribosome after the release of the completed protein and trapping the release factors. By genome mining, we have identified 71 PrAMPs encoded in insect genomes as pre-pro-polyproteins. Having chemically synthesized and tested the activity of 26 peptides, we demonstrate that despite significant sequence variation in the N-terminal sequence, the majority of the PrAMPs that retain the conserved C-terminal sequence of Api are able to trap the ribosome at the stop codons and induce stop codon readthrough—all hallmarks of Type II PrAMP mode of action. Some of the characterized PrAMPs exhibit superior antibacterial activity in comparison with Api. The newly solved crystallographic structures of the ribosome complexed with Api and with the more active peptide Fva1 from the stingless bee demonstrate the universal placement of the PrAMPs’ C-terminal pharmacophore in the post-release ribosome despite variations in their N-terminal sequence.

Huang, Weiping (ORCID:0000000273063550)↗
DOE OSTI2020

Generation of ionic liquid tolerant Pseudomonas putida KT2440 strains via adaptive laboratory evolution

Although the use of ionic liquids (ILs) for the pretreatment of lignocellulosic biomass has been limited due to high costs, recent efforts to develop low-cost protic ILs show promise for achieving cost-effectiveness for biorefineries. However, an additional challenge remains in that ILs present in biomass hydrolysates are toxic to most microbial hosts, resulting in poor growth phenotypes. To address this issue, we applied an adaptive laboratory evolution (ALE) approach for tolerizing Pseudomonas putida KT2440, an industrially relevant bacterial host, to two low-cost ILs (triethanolammonium acetate [TEOH][OAc] and triethylammonium hydrogen sulfate [TEA][HS]). After continuous cultivations with gradually increased IL levels, we obtained evolved strains showing significant improvements in their growth performance under high concentrations of the ILs (maximum 4% [TEOH][OAc] and 8% [TEA][HS], in w/v) at which the wild-type strain cannot grow. Sequencing of evolved strains revealed multiple regions where mutations were associated with improved performance in minimal media conditions (relA, gacS, oprB/PP_1446, fleQ, tktA, and uvrY/PP_4100) and in IL-specific conditions (PP_5350, PP_4929/emrE, oprD, and PP_5324). We further validated the causality of the PP_5350 and emrE genes for improved IL tolerance via reverse engineering and transcriptomic analysis. Here, a common mutation in the PP_5350 gene, encoding a RpiR family transcriptional regulator, was shown to significantly upregulate the glyoxylate cycle for efficient acetate catabolism. In addition, it was suggested that the emrE gene encodes an efflux pump which can export [TEA][HS]. Finally, the cultivation of two of the best performing evolved strains with IL-treated biomass hydrolysates demonstrated their considerable potential to be used as platform strains. Taken as a whole, this work provides strains for utilization of IL-treated biomass and a mechanistic understanding that could be further leveraged to develop efficient microbial bioprocesses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mixed polyamide and polyester upcycling via chemical autoxidation and engineered Pseudomonas putida

Polyamides, such as nylons, are often used in multi-component materials, like textiles and packaging, and are accompanied with unique recycling challenges. Recently, autoxidation and bioconversion has emerged as a tandem approach for the conversion of mixed plastics waste to single products, however the fate of polyamides in these processes is unknown. Here, we optimized the autoxidation of nylon-6 and nylon-6,6 depolymerization, achieving >92 mol% nitrogen recovery from both substrates, predominantly as acetamide, and 20–27 mol% carbon recovery (not including acetamide). Experiments with 13 C-labeled acetic acid demonstrated that the carbon in acetamide was solvent derived. Autoxidation of mixed nylon-6 and poly(ethylene terephthalate) (PET) post-consumer fibers resulted in similar carbon and nitrogen recoveries from nylon, while PET was depolymerized to terephthalic acid (TPA) at >65 C-mol% recovery. Next, we engineered Pseudomonas putida KT2440 to utilize acetamide as the sole carbon and nitrogen source for growth through the constitutive expression of genes encoding amidase enzymes, including a native amidase (PP_0613) shown to be active on C 2 –C 4 amides. Heterologous chromosomal expression of amiE, encoding the amidase from P. aeruginosa, was found to be superior to PP_0613 constitutive expression in genome integrated strains. Prior engineering to enable TPA conversion to β-ketoadipate pathway intermediate protocatechuate was leveraged and combined with deletion of pcaD to produce muconolactone as a product. Finally, a stacked strain engineered for conversion of acetamide, TPA, and DCAs was evaluated on the reaction product from autoxidation of mixed post-consumer nylon and PET fibers without any supplemental nitrogen, achieving quantitative yields in the presence of supplemental carbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Glycosyltransferase family 47 (GT47) proteins in plants and animals

Glycosyltransferases (GTs) are carbohydrate-active enzymes that are encoded by the genomes of organisms spanning all domains of life. GTs catalyze glycosidic bond formation, transferring a sugar monomer from an activated donor to an acceptor substrate, often another saccharide. GTs from family 47 (GT47, PF03016) are involved in the synthesis of complex glycoproteins in mammals and insects and play a major role in the synthesis of almost every class of polysaccharide in plants, with the exception of cellulose, callose, and mixed linkage β-1,3/1,4-glucan. GT47 enzymes adopt a GT-B fold and catalyze the formation of glycosidic bonds through an inverting mechanism. Unlike animal genomes, which encode few GT47 enzymes, plant genomes contain 30 or more diverse GT47 coding sequences. With our current knowledge of the GT47 family across plant species brings us an interesting view, showcasing how members exhibit a great diversity in both donor and acceptor substrate specificity, even for members that are classified in the same phylogenetic clade. Thus, we discuss how plant GT47 family members represent a great case to study the relationship between substrate specificity, protein structure, and protein evolution. Most of the plant GT47 enzymes that are identified to date are involved in biosynthesis of plant cell wall polysaccharides, including xyloglucan, xylan, mannan, and pectins. This indicates unique and crucial roles of plant GT47 enzymes in cell wall formation. The aim of this review is to summarize findings about GT47 enzymes and highlight new challenges and approaches on the horizon to study this family.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗