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At least 343 records · Page 19

Genetic Interactions Between Brassinosteroid-Inactivating P450s and Photomorphogenic Photoreceptors in Arabidopsis thaliana

Plants use light as a source of information via a suite of photomorphogenic photoreceptors to optimize growth in response to their light environment. Growth-promoting hormones such as brassinosteroids also can modulate many of these responses. BAS1 and SOB7 are brassinosteroid-catabolizing P450s in Arabidopsis thaliana that synergistically/redundantly modulate photomorphogenic traits such as flowering time. The role of BAS1 and SOB7 in photomorphogenesis has been investigated by studying null-mutant genetic interactions with the photoreceptors phyA, phyB, and cry1 with regard to seed germination and flowering time. The removal of BAS1 and/or SOB7 rescued the low germination rate of the phyA-211 phyB9 double-null mutant. With regard to floral induction, bas1-2 and sob7-1 showed a complex set of genetic interactions with photoreceptor-null mutants. Histochemical analysis of transgenic plants harboring BAS1: BAS1-GUS and SOB7:SOB7-GUS translational fusions under the control of their endogenous promoters revealed overlapping and distinct expression patterns. BAS1’s expression in the shoot apex increases during the phase transition from short-to-long-day growth conditions and requires phyB in red light. In summary, BAS1 and SOB7 displayed both simple and complex genetic interactions with the phytochromes in a plant-stage specific manner.

54 ENVIRONMENTAL SCIENCES↗

Genome-wide Association Study Identifies Candidate Loci with Major Contributions to the Genetic Control of Pod Morphological Traits in Snap Bean

Snap beans are cultivars of common bean (Phaseolus vulgaris) that are cultivated for their fleshy immature pods that exhibit a wide diversity of pod shapes and sizes. The genetic basis of the snap bean pod shape is complex and involves the interaction of multiple genes. This study used a snap bean diversity panel composed of heirloom and improved cultivars used in North America and genome-wide association studies (GWAS) to investigate the genetic basis of pod morphological characteristics, including length, width, height, width/height ratio, and coefficients of variation (CVs). The GWAS detected multiple genomic regions associated with each pod trait, with a total of 20 quantitative trait loci (QTLs) for pod length, 9 for pod width, 14 for pod height, and 10 for pod width/height ratio. Regarding theCVof each pod trait, genome-wide association analyses detected six QTL for lengthCVs, five for widthCVs, 15 for heightCVs, and six for width/height ratioCVs. Thirteen regions in seven chromosomes were associated with two or more pod traits. Eighteen QTLs for pod traits in this study colocated with previously reported QTLs for pod and seed traits. The QTL intervals encompass gene models with homologues in other species that are involved in the control of developmental processes. These results capture the complex nature of the genetic control of snap bean pod traits and confirm the significance of genomic regions harboring overlapping QTLs identified in this and other studies. The phenotypic expression of pod traits in snap bean appears to be under the control of a few genomic regions with a strong effect with additional contributions of multiple small-effect regions. Validation of the function of the candidate genes identified in associated regions will contribute to our understanding of legume pod development.

Agriculture↗

Molecular Genetic Analysis of Activation-Tagged Transcription Factors Thought to be Involved in Photomorphogenesis

This is a final report for Department of Energy Grant No. DE-FG02-08ER15927 entitled “Molecular Genetic Analysis of Activation-Tagged Transcription Factors Thought to be Involved in Photomorphogenesis”. Based on our preliminary photobiological and genetic analysis of the sob1-D mutant, we hypothesized that OBP3 is a transcription factor involved in both phytochrome and cryptochrome-mediated signal transduction. In addition, we hypothesized that OBP3 is involved in auxin signaling and root development. Based on our preliminary photobiological and genetic analysis of the sob2-D mutant, we also hypothesized that a related gene, LEP, is involved in hormone signaling and seedling development.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic Control of Flowering in Switchgrass (Final Technical Report)

Lignocellulosic biomass is poised to become a significant source of renewable fuel in the United States, and perennial grasses such as switchgrass are likely to provide a significant amount of this biomass. A decline in biomass yield is typically observed in switchgrass immediately following completion of flowering. In the northern part of the country, flowering occurs in switchgrass around the time that biomass yield peaks, and the approximately two-month growing season for biomass accumulation can be lost due to a flowering event. If flowering time can be delayed about 4-5 weeks, biomass yield can potentially increase 30-50%. To develop a rational strategy for creating improved switchgrass with late flowering, it would be beneficial to have a better understanding of the genes that control flowering time in switchgrass. The proposed research aims to dissect the genetic control of the flowering time of switchgrass. Through genetic, genomic, and bioinformatics approaches, key genes involved in the flowering pathways such as photoperiod and circadian control have been identified. The obtained research information will help further elucidate the molecular mechanisms underlying anthesis phenotypes of switchgrass. The genetic variants related to floral development identified through the project can support a long-term goal of developing late flowering varieties of switchgrass that fully utilize the growing season and achieve high biomass yield. The resources generated from the project have been timely distributed to the community via professional meetings and publications. Graduate students and postdoctoral researchers have been trained through working on the project.

09 BIOMASS FUELS↗

GenSpec: A Genetic Algorithm for Neutron Energy Spectrum Adjustment

Presented in this report is the description of a new method for neutron energy spectrum adjustment which uses a genetic algorithm to minimize the difference between calculated and measured reaction probabilities. The measured reaction probabilities are found using neutron activation analysis. The method adjusts a trial spectrum provided by the user which is typically calculated using a neutron transport code such as MCNP. Observed benefits of this method over currently existing methods include the reduction in unrealistic artefacts in the spectral shape as well as a reduced sensitivity to increases in the energy resolution of the derived spectrum. This report presents the adjustment results for various spectrum altering bucket environments in the central cavity of the Annular Core Research Reactor, as well as the adjustment results for the spectrum in the Sandia Pulse Reactor III. In each case, the results are compared to those generated using LSL-M2, which is a code commonly used for the purpose of spectrum adjustment. The genetic algorithm produces spectrum-averaged reaction probabilities with agreement to measured values, and comparable to those resulting from LSL-M2. The true benefit to this method, the reduction of shape artefacts in the spectrum, is difficult to quantify but can be clearly seen in the comparison of the final adjustments. Beyond these preliminary results, this report also gives a thorough description of the genetic algorithm and presents instructions for running the code using the graphical user interface. In its present state, the code does not provide uncertainties or correlations for the adjusted spectrum. This capability is currently being added, and will be presented in future work.

42 ENGINEERING↗

Genetics and Genomics of Pathogen Resistance in Switchgrass

This project investigates the genetic and genomic bases of resistance/tolerance to disease in switchgrass (Panicum virgatum) populations developed as bioenergy feedstock. The focus is placed populations adapted to the Central Great Plains derived from the hybridization of upland and lowland ecotypes, represented by cultivars Summer and Kanlow, respectively. Resistance was investigated against the rust disease caused by the fungus Puccinia novo-panici (syn. P emaculata) and mosaic disease caused by the virus complex of Panicum mosaic virus and its satellite. Objectives of the project were: 1) to elucidate the genetic and genomic bases of resistance/tolerance in locally adapted upland and lowland switchgrass breeding populations with contrasting disease symptoms under field conditions; 2) determine the molecular underpinnings of why cv Kanlow has broad resistance/tolerance to pathogens; and 3) discover the molecular differences that permit systemic viral infections in some switchgrass plants but not in other genetically-related plants.

09 BIOMASS FUELS↗

Developing Advanced Genetic and Synthetic Biology Tools for Improved Algae Productivity

Under the UCSD-led Productivity Enhanced Algae and ToolKits (PEAK) project we sought to develop tools to enable the production of valuable co-products, as well as strategies to decrease the cost of cultivation, with an intended outcome of enabling the economic production of algae-based biofuel. We have developed new genetic tools and high throughput selection methods for eukaryotic green algae and used them to express a high value recombinant protein; a growth factor known as Osteopontin (OPN). Recombinant OPN protein expression levels were improved through a newly developed rapid breeding and mutagenesis strain improvement method to generate a robust strain capable of growing in outdoors raceway conditions in brackish water that tolerated high pH and large temperature swings. We further applied the new genetic tools to express recombinant protein in a recently bioprospected strain with even more robust growth characteristics. In response to the COVID-19 pandemic we used our improved workflow to rapidly express, purify, and characterize a recombinant SARS-CoV-2 spike protein Receptor Binding Domain (RBD) and demonstrate that it functionally interacts with its cognate human host receptor ACE2. The newly identified extremophile strain Chlamydomonas sp (402), both mating type (mt+) and mating type (mt-), have been deposited in the Chlamydomonas Resource Center (https://www.chlamycollection.org/), making them available world-wide with no restrictions. In addition, all of genetic tools are also deposited at this site and are also available world-wide with no restrictions.

09 BIOMASS FUELS↗

Development of Genetic Algorithm Based Multi-Objective Plant Reload Optimization Platform

The U.S. nuclear industry is facing a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light-water reactor nuclear power plant operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed in the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. The Light Water Reactor Sustainability Program promotes a wide range of research and development activities to maximize both the safety and economic efficiency of nuclear power plants through improved scientific understanding, especially given that many plants are now considering second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: Deploy methodologies and technologies that better represent safety margins and cost and safety factors; Develop advanced applications that enable cost-effective plant operations. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. This report summarizes genetic-algorithm-based multi-objective fuel reload optimization activities, specifically: Developing the non-dominated sorting genetic algorithm II optimizer in the Risk Analysis and Virtual ENviroment (RAVEN); Demonstrating and validating the developed non-dominated sorting genetic algorithm II optimizer using benchmark optimization problems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Building a framework to genetically characterize “feather spots” and understand demographic impacts of solar energy sites on migratory bird populations

The lack of data on the impact of utility-scale solar facilities on avian species and populations adds to the cost of siting and operation. As much as 32 percent of the avian biological material (feathers and carcasses) recovered from solar facilities remain unidentified, because they often take the form of “feather spots”. Feather spots are remains of impacted animals that can be separated into two broad categories: 1) those remains that may be visually identified to a species, or 2) those that cannot be visually identified to a species due to degradation from the environment and/or scavenger activity (listed as “unknown”). Even when feather spots can be identified to species, they cannot be visually assigned to particular breeding populations. In some cases, it is unknown whether multiple feather spots represent single or multiple individuals. This project’s objectives were to: 1. Use a developed, genetic-based technique to identify and determine the species, population of origin, and number of individuals found in feather spots recovered from solar facilities. 2. Implement collected data and resulting analyses to develop a publicly accessible web-based decision-making tool that can be used by the solar industry, regulators and other stakeholders to inform siting, mitigation, and conservation management efforts. 3. Establish a not-for-profit fee-for-service center at UCLA to ensure collection and identification of feather spots continue after the project period of performance. During the Project Period, we proposed to establish a pipeline for collecting, transporting, and storing of avian biological material collected at solar facilities and the collection and identification of feather spots to species and individual. We proposed the development of a genetic-based framework that would recover viable DNA from feather spots, amplify this DNA (i.e., make millions of copies of the original DNA), and use it to match the resulting sequences to a national database of known species of birds. The result would be the identification of feathers spots that were previously unidentified, and the incorporation of these samples into a larger database that included all samples recovered from solar facilities. The resulting report (below) details the result of this work and its alignment with proposed activities. We proposed the use of the data collected to assess the comparative risk to specific species or populations of species from solar facilities. For some species, we have already identified genomic markers of specific breeding populations and developed “genoscapes,” maps of unique genetic variation across the full breeding range of a species. We used these (previously and newly developed) genoscapes to probabilistically link a feather spot to the specific breeding populations from which it originated (assignment probabilities range from 75%-100% depending on species and population groups). For those species without genoscapes, we developed a vulnerability and susceptibility estimate that determines the relative local and regional risk to populations that are in geographic proximity to solar facilities, using citizen science data (Breeding Bird Survey (BBS) and eBird). These two feather spot processing pipelines (see Figure 1 below) provide quantitative estimates as to the numbers of individuals from a given population of origin that are affected by solar facilities, and ultimately can reduce costs to the consumer by reducing the industry costs associated with mitigation and siting strategies for future solar energy development.

14 SOLAR ENERGY↗

The Complete Genome and Physiological Analysis of the Microbialite-Dwelling Agrococcus pavilionensis sp. nov; Reveals Genetic Promiscuity and Predicted Adaptations to Environmental Stress

Members of the bacterial genus Agrococcus are globally distributed and found across highly diverse environments including forests, deserts, potatoes, coal mines, and cheese. Despite their widespread occurrence, the extent of their genetic diversity is poorly explored and no complete reference genomes are available. Using whole-genome analysis, chemotaxonomic markers, morphology, and 16S rDNA phylogeny we characterize the new species Agrococcus pavilionensis strain RW1, and provide the first complete genome from a member of the genus Agrococcus. The A. pavilionensis genome consists of one chromosome (2,627,177 bp) as well as two plasmids (HC-CG1 1,427 bp, and LC-RRW783 31,795 bp) that reveal considerable genetic promiscuity, and include a prophage-like element on the main chromosome, and plasmid genes involved in integration, transposition, and heavy-metal stress. Agrococcus pavilionensis strain RW1 differs from other members of the genus in having a novel phospholipid fatty acid iso-C15:1Δ 4 , ß-galactosidase activity, filamentous growth under carbon stress, and amygdalin utilization. Both Agrococcus pavilionensis and Agrococcus lahaulensis encode a gene cluster that is likely involved in the synthesis of carotenoids and the production of the characteristic yellow pigmentation found in Agrococcus spp. The widespread occurrence of this genus across a remarkable range of diverse environments, and its genetic plasticity, hints at the ecological significance of Agrococcus spp.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic and Genetic Insights Into a Cosmopolitan Fungus, Paecilomyces variotii (Eurotiales)

Species in the genus Paecilomyces , a member of the fungal order Eurotiales, are ubiquitous in nature and impact a variety of human endeavors. Here, the biology of one common species, Paecilomyces variotii , was explored using genomics and functional genetics. Sequencing the genome of two isolates revealed key genome and gene features in this species. A striking feature of the genome was the two-part nature, featuring large stretches of DNA with normal GC content separated by AT-rich regions, a hallmark of many plant-pathogenic fungal genomes. These AT-rich regions appeared to have been mutated by repeat-induced point (RIP) mutations. We developed methods for genetic transformation of P. variotii , including forward and reverse genetics as well as crossing techniques. Using transformation and crossing, RIP activity was identified, demonstrating for the first time that RIP is an active process within the order Eurotiales. A consequence of RIP is likely reflected by a reduction in numbers of genes within gene families, such as in cell wall degradation, and reflected by growth limitations on P. variotii on diverse carbon sources. Furthermore, using these transformation tools we characterized a conserved protein containing a domain of unknown function (DUF1212) and discovered it is involved in pigmentation.

59 BASIC BIOLOGICAL SCIENCES↗

Setaria Comes of Age: Meeting Report on the Second International Setaria Genetics Conference

Setaria viridis is an emerging model for cereal and bioenergy grasses because of its short stature, rapid life cycle and expanding genetic and genomic toolkits. Its close phylogenetic relationship with economically important crops such as maize and sorghum positions Setaria as an ideal model system for accelerating discovery and characterization of crop genes that control agronomically important traits. The Second International Setaria Genetics Conference was held on March 6–8, 2017 at the Donald Danforth Plant Science Center, St. Louis, MO, United States to discuss recent technological breakthroughs and research directions in Setaria (presentation abstracts can be downloaded at https://www.brutnelllab.org/setaria). Here, we highlight topics presented in the conference including inflorescence architecture, C 4 photosynthesis and abiotic stress. Genetic and genomic toolsets including germplasm, mutant populations, transformation and gene editing technologies are also discussed. Since the last meeting in 2014, the Setaria community has matured greatly in the quality of research being conducted. Outreach and increased communication with maize and other plant communities will allow broader adoption of Setaria as a model system to translate fundamental discovery research to crop improvement.

54 ENVIRONMENTAL SCIENCES↗

Biocontainment of Genetically Engineered Algae

Algae (including eukaryotic microalgae and cyanobacteria) have been genetically engineered to convert light and carbon dioxide to many industrially and commercially relevant chemicals including biofuels, materials, and nutritional products. At industrial scale, genetically engineered algae may be cultivated outdoors in open ponds or in closed photobioreactors. In either case, industry would need to address a potential risk of the release of the engineered algae into the natural environment, resulting in potential negative impacts to the environment. Genetic biocontainment strategies are therefore under development to reduce the probability that these engineered bacteria can survive outside of the laboratory or industrial setting. These include active strategies that aim to kill the escaped cells by expression of toxic proteins, and passive strategies that use knockouts of native genes to reduce fitness outside of the controlled environment of labs and industrial cultivation systems. Several biocontainment strategies have demonstrated escape frequencies below detection limits. However, they have typically done so in carefully controlled experiments which may fail to capture mechanisms of escape that may arise in the more complex natural environment. The selection of biocontainment strategies that can effectively kill cells outside the lab, while maintaining maximum productivity inside the lab and without the need for relatively expensive chemicals will benefit from further attention.

59 BASIC BIOLOGICAL SCIENCES↗

Overcoming genetic paucity of Camelina sativa : possibilities for interspecific hybridization conditioned by the genus evolution pathway

Camelina or false flax (Camelina sativa) is an emerging oilseed crop and a feedstock for biofuel production. This species is believed to originate from Western Asian and Eastern European regions, where the center of diversity of the Camelina genus is located. Cultivated Camelina species arose via a series of polyploidization events, serving as bottlenecks narrowing genetic diversity of the species. The genetic paucity of C. sativa is foreseen as the most crucial limitation for successful breeding and improvement of this crop. A potential solution to this challenge could be gene introgression from Camelina wild species or from resynthesized allohexaploid C. sativa. However, both approaches would require a complete comprehension of the evolutionary trajectories that led to the C. sativa origin. Although there are some studies discussing the origin and evolution of Camelina hexaploid species, final conclusions have not been made yet. Here, we propose the most complete integrated evolutionary model for the Camelina genus based on the most recently described findings, which enables efficient improvement of C. sativa via the interspecific hybridization with its wild relatives. We also discuss issues of interspecific and intergeneric hybridization, aimed on improving C. sativa and overcoming the genetic paucity of this crop. The proposed comprehensive evolutionary model of Camelina species indicates that a newly described species Camelina neglecta has a key role in origin of tetra- and hexaploids, all of which have two C. neglecta-based subgenomes. Understanding of species evolution within the Camelina genus provides insights into further research on C. sativa improvements via gene introgression from wild species, and a potential resynthesis of this emerging oilseed crop.

09 BIOMASS FUELS↗

classLog: Logistic regression for the classification of genetic sequences

Introduction Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in realtime genomic contact tracing and surveillance. Under this paradigm, unprecedented volumes of data are generated that require rapid analysis to provide meaningful inference. Methods We present a machine learning logistic regression pipeline that can assign classifications to genetic sequence data. The pipeline implements an intuitive and customizable approach to developing a trained prediction model that runs in linear time complexity, generating accurate output rapidly, even with incomplete data. Our approach was benchmarked against porcine respiratory and reproductive syndrome virus (PRRSv) and swine H1 influenza A virus (IAV) datasets. Trained classifiers were tested against sequences and simulated datasets that artificially degraded sequence quality at 0, 10, 20, 30, and 40%. Results When applied to a poor-quality sequence data, the classifier achieved between >85% to 95% accuracy for the PRRSv and the swine H1 IAV HA dataset and this increased to near perfect accuracy when using the full dataset. The model also identifies amino acid positions used to determine genetic clade identity through a feature selection ranking within the model. These positions can be mapped onto a maximum-likelihood phylogenetic tree, allowing for the inference of clade defining mutations. Discussion Our approach is implemented as a python package with code available at https://github.com/flu-crew/classLog .

Zeller, Michael A.↗

Stability Analysis of Parameter Varying Genetic Toggle Switches Using Koopman Operators

The genetic toggle switch is a well known model in synthetic biology that represents the dynamic interactions between two genes that repress each other. The mathematical models for the genetic toggle switch that currently exist have been useful in describing circuit dynamics in rapidly dividing cells, assuming fixed or time-invariant kinetic rates. There is a growing interest in being able to model and extend synthetic biological function for growth conditions such as stationary phase or during nutrient starvation. As cells transition from one growth phase to another, kinetic rates become time-varying parameters. In this paper, we propose a novel class of parameter varying nonlinear models that can be used to describe the dynamics of genetic circuits, including the toggle switch, as they transition from different phases of growth. We show that there exists unique solutions for this class of systems, as well as for a class of systems that incorporates the microbial phenomena of quorum sensing. Further, we show that the domain of these systems, which is the positive orthant, is positively invariant. We also showcase a theoretical control strategy for these systems that would grant asymptotic monostability of a desired fixed point. We then take the general form of these systems and analyze their stability properties through the framework of time-varying Koopman operator theory. A necessary condition for asymptotic stability is also provided as well as a sufficient condition for instability. A Koopman control strategy for the system is also proposed, as well as an analogous discrete time-varying Koopman framework for applications with regularly sampled measurements.

Harrison, Jamiree (ORCID:0000000265351579)↗

Change in Emiliania huxleyi Virus Assemblage Diversity but Not in Host Genetic Composition during an Ocean Acidification Mesocosm Experiment

Effects of elevated pCO₂ on Emiliania huxleyi genetic diversity and the viruses that infect E. huxleyi (EhVs) have been investigated in large volume enclosures in a Norwegian fjord. Triplicate enclosures were bubbled with air enriched with CO₂ to 760 ppmv whilst the other three enclosures were bubbled with air at ambient pCO₂ ; phytoplankton growth was initiated by the addition of nitrate and phosphate. E. huxleyi was the dominant coccolithophore in all enclosures, but no difference in genetic diversity, based on DGGE analysis using primers specific to the calcium binding protein gene ( gpa ) were detected in any of the treatments. Chlorophyll concentrations and primary production were lower in the three elevated pCO₂ treatments than in the ambient treatments. However, although coccolithophores numbers were reduced in two of the high- pCO₂ treatments; in the third, there was no suppression of coccolithophores numbers, which were very similar to the three ambient treatments. In contrast, there was considerable variation in genetic diversity in the EhVs, as determined by analysis of the major capsid protein ( mcp ) gene. EhV diversity was much lower in the high- pCO₂ treatment enclosure that did not show inhibition of E. huxleyi growth. Since virus infection is generally implicated as a major factor in terminating phytoplankton blooms, it is suggested that no study of the effect of ocean acidification in phytoplankton can be complete if it does not include an assessment of viruses.

Virology↗

Pyrrolysyl-tRNA Synthetase, an Aminoacyl-tRNA Synthetase for Genetic Code Expansion

Genetic code expansion (GCE) has become a central topic of synthetic biology. GCE relies on engineered aminoacyl-tRNA synthetases (aaRSs) and a cognate tRNA species to allow codon reassignment by co-translational insertion of non-canonical amino acids (ncAAs) into proteins. Introduction of such amino acids increases the chemical diversity of recombinant proteins endowing them with novel properties. Such proteins serve in sophisticated biochemical and biophysical studies both in vitro and in vivo, they may become unique biomaterials or therapeutic agents, and they afford metabolic dependence of genetically modified organisms for biocontainment purposes. In the Methanosarcinaceae the incorporation of the 22nd genetically encoded amino acid, pyrrolysine (Pyl), is facilitated by pyrrolysyl-tRNA synthetase (PylRS) and the cognate UAG-recognizing tRNAPyl. This unique aaRS•tRNA pair functions as an orthogonal translation system (OTS) in most model organisms. The facile directed evolution of the large PylRS active site to accommodate many ncAAs, and the enzyme’s anticodon-blind specific recognition of the cognate tRNAPyl make this system highly amenable for GCE purposes. The remarkable polyspecificity of PylRS has been exploited to incorporate >100 different ncAAs into proteins. Here we review the Pyl-OT system and selected GCE applications to examine the properties of an effective OTS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗