Diverse organic-mineral associations in Jezero crater, Mars.

The presence and distribution of preserved organic matter on the surface of Mars can provide key information about the Martian carbon cycle and the potential of the planet to host life throughout its history. Several types of organic molecules have been previously detected in Martian meteorites1 and at Gale crater, Mars2-4. Evaluating the diversity and detectability of organic matter elsewhere on Mars is important for understanding the extent and diversity of Martian surface processes and the potential availability of carbon sources1,5,6. Here we report the detection of Raman and fluorescence spectra consistent with several species of aromatic organic molecules in the Máaz and Séítah formations within the Crater Floor sequences of Jezero crater, Mars. We report specific fluorescence-mineral associations consistent with many classes of organic molecules occurring in different spatial patterns within these compositionally distinct formations, potentially indicating different fates of carbon across environments. Our findings suggest there may be a diversity of aromatic molecules prevalent on the Martian surface, and these materials persist despite exposure to surface conditions. These potential organic molecules are largely found within minerals linked to aqueous processes, indicating that these processes may have had a key role in organic synthesis, transport or preservation.

Utilizing MiSeq Sequencing to Detect Circulating microRNAs in Plasma for Improved Lung Cancer Diagnosis.

Non-small cell lung cancer (NSCLC) is a major contributor to cancer-related deaths, but early detection can reduce mortality. NSCLC comprises mainly adenocarcinoma (AC) and squamous cell carcinoma (SCC). Circulating microRNAs (miRNAs) in plasma have emerged as promising biomarkers for NSCLC. However, existing techniques for analyzing miRNAs have limitations, such as restricted target detection and time-consuming procedures. The MiSeqDx System has been shown to overcome these limitations, making it a promising tool for routine clinical settings. We investigated whether the MiSeqDx could profile cell-free circulating miRNAs in plasma and diagnose NSCLC. We sequenced RNA from the plasma of patients with AC and SCC and from cancer-free smokers using the MiSeqDx to profile and compare miRNA expressions. The MiSeqDx exhibits high speed and accuracy when globally analyzing plasma miRNAs. The entire workflow, encompassing RNA to data analysis, was completed in under three days. We also identified panels of plasma miRNA biomarkers that can diagnose NSCLC with 67% sensitivity and 68% specificity, and detect SCC with 90% sensitivity and 94% specificity, respectively. This study is the first to demonstrate that rapid profiling of plasma miRNAs using the MiSeqDx has the potential to offer a straightforward and effective method for the early detection and classification of NSCLC.

Aptamer-functionalized 2D photonic crystal hydrogels for detection of adenosine.

Aptamer-functionalized two-dimensional photonic crystal (2DPC) hydrogels are reported for the detection of adenosine (AD). As a molecular recognition group, an AD-binding aptamer was covalently attached to 2DPC hydrogels. This aptamer selectively and sensitively binds AD, changing the conformation of the aptamer from a long single-stranded structure (AD-free conformation) to a short hairpin loop structure (AD-bound conformation). The AD-binding-induced changes of aptamer conformation reduced the volume of the 2DPC hydrogels and decreased the interparticle spacing of the 2DPC embedded in the hydrogel network. The particle spacing changes being dependent on AD concentration were determined by measuring 2DPC light diffraction using a simple laser pointer. The 2DPC hydrogel sensor showed a large particle spacing decrease of ~ 110 nm in response to 1 mM AD in phosphate-buffered saline (PBS). The linear range of determination of AD was 0.1 nM to 1 mM and the limit of detection was 0.09 nM. The hydrogel sensor response for real samples was then validated in diluted fetal bovine serum (FBS) and human urine. The average % difference in particle spacing changes measured between diluted FBS and pure PBS was only 3.99%. In diluted human urine, the recoveries for the detection of AD were 95-101% and the relative standard deviations were 4.9-7.8%. The results demonstrate the potential applicability of the hydrogel sensor for real samples. This sensing concept, using the aptamer-functionalized 2DPC hydrogels, allows for a simple, sensitive, selective, and reversible detection of AD. It may enable sensor development for a wide variety of analytes by simply changing the aptamer recognition group.

Mechanisms by Which Organic Solvent Exchange Transforms Responsive Pure Protein Hydrogels into Responsive Organogels.

Responsive pure protein organogel sensors and catalysts are fabricated by replacing the aqueous mobile phase of protein hydrogels with pure ethylene glycol (EG). Exchanging water for EG causes irreversible volume phase transitions (VPT) in bovine serum albumin (BSA) polymers; however, BSA hydrogel and organogel sensors show similar volume responses to protein-ligand binding. This work elucidates the mechanisms involved in this enabling irreversible VPT by examining the protein secondary structure, hydration, and protein polymer morphology. Organogel proteins retain their native activity because their secondary structure and hydration shell are relatively unperturbed by the EG exchange. Conversely, the decreasing solvent quality initiates polymer phase separation to minimize the BSA polymer surface area exposed to EG, thus decreasing distances between BSA polymer strands. These protein polymer morphology changes promote interprotein interactions between BSA polymer strands, which increase the effective polymer cross-link density and prevent organogel swelling as the mobile phase is exchanged back to water.

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics.

BACKGROUND: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. RESULTS: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. CONCLUSIONS: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.

Cell-based reference samples designed with specific differences in microRNA biomarkers.

BACKGROUND: We demonstrate the feasibility of creating a pair of reference samples to be used as surrogates for clinical samples measured in either a research or clinical laboratory setting. The reference sample paradigm presented and evaluated here is designed to assess the capability of a measurement process to detect true differences between two biological samples. Cell-based reference samples can be created with a biomarker signature pattern designed in silico. Clinical laboratories working in regulated applications are required to participate in proficiency testing programs; research laboratories doing discovery typically do not. These reference samples can be used in proficiency tests or as process controls that allow a laboratory to evaluate and optimize its measurement systems, monitor performance over time (process drift), assess changes in protocols, reagents, and/or personnel, maintain standard operating procedures, and most importantly, provide evidence for quality results. RESULTS: The biomarkers of interest in this study are microRNAs (miRNAs), small non-coding RNAs involved in the regulation of gene expression. Multiple lung cancer associated cell lines were determined by reverse transcription (RT)-PCR to have sufficiently different miRNA profiles to serve as components in mixture designs as reference samples. In silico models based on the component profiles were used to predict miRNA abundance ratios between two different cell line mixtures, providing target values for profiles obtained from in vitro mixtures. Two reference sample types were tested: total RNA mixed after extraction from cell lines, and intact cells mixed prior to RNA extraction. MicroRNA profiling of a pair of samples composed of extracted RNA derived from these cell lines successfully replicated the target values. Mixtures of intact cells from these lines also approximated the target values, demonstrating potential utility as mimics for clinical specimens. Both designs demonstrated their utility as reference samples for inter- or intra-laboratory testing. CONCLUSIONS: Cell-based reference samples can be created for performance assessment of a measurement process from biomolecule extraction through quantitation. Although this study focused on miRNA profiling with RT-PCR using cell lines associated with lung cancer, the paradigm demonstrated here should be extendable to genome-scale platforms and other biomolecular endpoints.

Ultraviolet Resonance Raman Spectroscopic Markers for Protein Structure and Dynamics.

UV resonance Raman (UVRR) spectroscopy is a powerful tool for investigating the structure of biological molecules, such as proteins. Numerous UVRR spectroscopic markers that provide information on the structure and environment of the protein backbone and of amino acid side chains have recently been discovered. Combining these UVRR markers with hydrogen-deuterium exchange and advanced statistics is a powerful tool for studying protein systems, including the structure and formation mechanism of protein aggregates and amyloid fibrils. These techniques allow crucial new insights into the structure and dynamics of proteins, such as polyglutamine peptides, which are associated with 10 different neurodegenerative diseases. Here we summarize the spectroscopic structural markers recently developed and the important insights they provide.

An analysis of research priority-setting at the World Health Organization - how mapping to a standard template allows for comparison between research priority-setting approaches.

BACKGROUND: A review of research priorities completed by WHO technical units was undertaken. Results of the mapping were recorded in a database that was used to generate analysis and compare research priorities and the different methodological approaches used in their development. METHODS: A total of 116 documents were reviewed for this study. The documents were published between 2002 and 2017 by the technical programmes of WHO headquarters and deposited in the institutional repository, IRIS. Research priorities were extracted from documents into a standard template and mapped to a five-category research cycle type framework defined in the WHO Strategy on Research for Health covering research to describe the research problem, identifying the cause and risk factors, developing solutions and new interventions, understanding the barriers to implementation, and evaluation of the impact of response. Details of the research priority methods were recorded. A database with user interface was created using Microsoft Excel 2010. RESULTS: A total of 2145 research priorities were extracted from the 116 documents meeting the inclusion criteria. The priorities specifically address 73 diseases/health topics. The document types were 26% Report, 22% WHO Guideline, 26% Research Prioritisation publication and 11% Meeting Notes. The most widely reported method used to identify priorities was expert consultation. Expert consultation was used to identify 86% of the priorities categorised here, with 26% (561) reporting it as the sole method; 52% (1111) explicitly listed a literature review as contributing to the identification of priorities. When the 2145 priorities were categorised across the research cycle framework, the largest portion (43%) addressed implementation challenges. The database is published here under an open access licence. CONCLUSION: Comparing research priorities between diseases/health topics requires standardisation and the research cycle type framework is one approach that can be applied across all the health topics found in public health. There is great variation in the use of research priority-setting methodology at WHO Headquarters. Therefore, a standard reporting approach, linked to established good practice, should be an area for future development by the WHO Global Health R&D Observatory. The database reported here can also be used to quickly access and analyse the research priorities for a specific health topic or to compare across a range of health topics.

UV Resonance Raman Investigation of Pentaerythritol Tetranitrate Solution Photochemistry and Photoproduct Hydrolysis.

Ultraviolet resonance Raman spectroscopy (UVRR) is being developed for standoff trace explosives detection. To accomplish this, it is important to develop a deep understanding of the accompanying UV excited photochemistry of explosives, as well as the impact of reactions on the resulting photoproducts. In the work here we used 229 nm excited UVRR spectroscopy to monitor the photochemistry of pentaerythritol tetranitrate (PETN) in acetonitrile. We find that solutions of PETN in CD3CN photodegrade with a quantum yield of 0.08 ± 0.02, as measured by high performance liquid chromatography (HPLC). The initial step in the 229 nm UV photolysis of PETN in CD3CN is cleavage of an O-NO2 bond to form NO2. The accompanying photoproduct is pentaerythritol trinitrate (PETriN), (CH2ONO2)3CCH2OH formed by photolysis of a single O-NO2. The resulting UVRR spectra show a dominant photoproduct band at ∼1308 cm-1, which derives from the symmetric stretch of dissolved NO2. This photoproduct NO2 is hydrolyzed by trace amounts of water, which downshifts this 1308 cm-1 NO2 Raman band due to the formation of molecular HNO3. The dissociation of HNO3 to NO3- in the presence of additional water results in an intense NO3- symmetric stretching UVRR band at 1044 cm-1.

Determination of Vertical Borehole and Geological Formation Properties using the Crossed Contour Method.

This paper presents a new method called the Crossed Contour Method for determining the effective properties (borehole radius and ground thermal conductivity) of a vertical ground-coupled heat exchanger. The borehole radius is used as a proxy for the overall borehole thermal resistance. The method has been applied to both simulated and experimental borehole Thermal Response Test (TRT) data using the Duct Storage vertical ground heat exchanger model implemented in the TRansient SYstems Simulation software (TRNSYS). The Crossed Contour Method generates a parametric grid of simulated TRT data for different combinations of borehole radius and ground thermal conductivity in a series of time windows. The error between the average of the simulated and experimental bore field inlet and outlet temperatures is calculated for each set of borehole properties within each time window. Using these data, contours of the minimum error are constructed in the parameter space of borehole radius and ground thermal conductivity. When all of the minimum error contours for each time window are superimposed, the point where the contours cross (intersect) identifies the effective borehole properties for the model that most closely represents the experimental data in every time window and thus over the entire length of the experimental data set. The computed borehole properties are compared with results from existing model inversion methods including the Ground Property Measurement (GPM) software developed by Oak Ridge National Laboratory, and the Line Source Model.

Aluminum Film-Over-Nanosphere Substrates for Deep-UV Surface-Enhanced Resonance Raman Spectroscopy.

We report here the first fabrication of aluminum film-over nanosphere (AlFON) substrates for UV surface-enhanced resonance Raman scattering (UVSERRS) at the deepest UV wavelength used to date (λex = 229 nm). We characterize the AlFONs fabricated with two different support microsphere sizes using localized surface plasmon resonance spectroscopy, electron microscopy, SERRS of adenine, tris(bipyridine)ruthenium(II), and trans-1,2-bis(4-pyridyl)-ethylene, SERS of 6-mercapto-1-hexanol (as a nonresonant molecule), and dielectric function analysis. We find that AlFONs fabricated with the 210 nm microspheres generate an enhancement factor of approximately 104-5, which combined with resonance enhancement of the adsorbates provides enhancement factors greater than 106. These experimental results are supported by theoretical analysis of the dielectric function. Hence our results demonstrate the advantages of using AlFON substrates for deep UVSERRS enhancement and contribute to broadening the SERS application range with tunable and affordable substrates.

Differential miRNA expressions in peripheral blood mononuclear cells for diagnosis of lung cancer.

Tremendous efforts have been made to develop cancer biomarkers by detecting circulating extracellular miRNAs directly released from tumors. Yet, none of the cell-free biomarkers has been accepted to be used for early detection of non-small cell lung cancer (NSCLC). Peripheral blood mononucleated cells (PBMCs) act as the first line of defense against malignancy in immune system, their dysfunction may occur as an early event in cancer immunogenicity or immune evasion. We proposed to investigate whether analysis of miRNA expressions of PBMCs has diagnostic value for NSCLC. We first used a microarray to analyze PBMCs of 16 stage I NSCLC patients and 16 cancer-free smokers, and identified seven PBMC miRNAs with a significantly altered expression level in NSCLC patients. In a training set of 84 NSCLC patients and 69 cancer-free smokers, a panel of two miRNAs (miRs-19b-3p and -29b-3p) were developed from the seven PBMC miRNAs, producing 72.62% sensitivity and 82.61% specificity in identifying NSCLC. Furthermore, the miRNAs could identify squamous cell lung carcinoma (SCC), a major type of NSCLC, with 80.00% sensitivity and 89.86% specificity. The expression levels of the miRNAs were independent of disease stage. In a testing set of 56 NSCLC patients and 46 controls, the performance of the biomarkers was reproducibly confirmed. The study presents the first in-depth analysis of PBMC miRNA profile of NSCLC patients. The assessment of PBMC miRNAs may provide a new diagnostic approach for the early detection of NSCLC.

Genome-wide small nucleolar RNA expression analysis of lung cancer by next-generation deep sequencing.

Emerging evidence indicates that small nucleolar RNAs (snoRNAs), a class of small noncoding RNAs, may play important function in tumorigenesis. Nonsmall-cell lung cancer (NSCLC) is the number one cancer killer for men and women. Systematically characterizing snoRNAs in NSCLC will develop biomarkers for its early detection and prognostication. We used next-generation deep sequencing to comprehensively characterize snoRNA profiles in 12 NSCLC tissues. We used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the findings in 40 surgical Stage I NSCLC specimens and 126 frozen NSCLC tissues of different stages. The 126 NSCLC tissues were divided into a training set and a testing set. Deep sequencing identified 458 snoRNAs, of which, 29 had a ≥3.0-fold expression level change in Stage I NSCLC tissues versus normal tissues. qRT-PCR analysis showed that 16 of 29 snoRNAs exhibited consistent changes with deep sequencing data. The 16 snoRNAs exhibited 0.75-0.94 area under receiver-operator characteristic curve values in distinguishing lung tumor from normal lung tissues (all ≤0.0001) with 70.0-95.0% sensitivity and 70.0-95.0% specificity. Six genes (snoRA47, snoRA68, snoRA78, snoRA21, snoRD28 and snoRD66) were identified whose expressions were associated with overall survival of the NSCLC patients. A prediction model consisting of three genes (snoRA47, snoRA68 and snoRA78) was developed in the training set of 77 cases, which could significantly predict overall survival of the NSCLC patients (p < 0.0001). The prognostic performance of the prediction model was confirmed in the testing set of 49 NSCLC patients. The identified snoRNA signatures may provide potential biomarkers for the early detection and prognostication of NSCLC.

Two-dimensional photonic crystal chemical and biomolecular sensors.

We review recent progress in the development of two-dimensional (2-D) photonic crystal (PC) materials for chemical and biological sensing applications. Self-assembly methods were developed in our laboratory to fabricate 2-D particle array monolayers on mercury and water surfaces. These hexagonal arrays strongly forward Bragg diffract light to report on their array spacings. By embedding these 2-D arrays onto responsive hydrogel surfaces, 2-D PC sensing materials can be fabricated. The 2-D PC sensors utilize responsive polymer hydrogels that are chemically functionalized to show volume phase transitions in selective response to particular chemical species. Novel hydrogels were also developed in our laboratory by cross-linking proteins while preserving their native structures to maintain their selective binding affinities. The volume phase transitions swell or shrink the hydrogels, which alter their 2-D array spacings, and shift their diffraction wavelengths. These shifts can be visually detected or spectrally measured. These 2-D PC sensing materials have been used for the detection of many analytes, such as pH, surfactants, metal ions, proteins, anionic drugs, and ammonia. We are exploring the use of organogels that use low vapor pressure ionic liquids as their mobile phases for sensing atmospheric analytes.

Removable interpenetrating network enables highly-responsive 2-D photonic crystal hydrogel sensors.

Responsive hydrogels functionalized with molecular recognition agents can undergo large volume changes upon interactions with specific chemical species. These responsive hydrogels can function as chemical sensing materials if the hydrogel volumes are monitored by using devices such as photonic crystals (PhC). An important criterion of merit is the responsiveness of these sensing hydrogels. Generally, hydrogel responsiveness is inversely proportional to the hydrogel crosslink density because the elastic constants scale with the crosslink density. The responsivities of these hydrogel sensors dramatically increase as their hydrogel crosslinker concentrations decrease. Unfortunately, the resulting highly responsive hydrogels become fragile at low crosslink densities, and are hard to fabricate and utilize. To temporarily increase the mechanical strengths of these highly responsive hydrogels we developed a method to incorporate a removable reinforcing interpenetrating hydrogel network. We demonstrate the utility of this approach by incorporating an interpenetrating PVA hydrogel within a weak, low crosslinked pH sensitive hydrogel through a freeze-thaw process. These interpenetrating PVA hydrogels are indefinitely stable at room temperature, but easily dissolved on transient heating to 70 °C. The pH sensing hydrogel response is unaffected by this incorporation and subsequent dissolution of the interpenetrating PVA hydrogel. These sacrificial hydrogels enable the fabrication and utilization of highly responsive hydrogel sensing materials.

A Photonic Crystal Protein Hydrogel Sensor for Candida albicans.

We report two-dimensional (2D) photonic crystal (PC) sensing materials that selectively detect Candida albicans (C. albicans). These sensors utilize Concanavalin A (Con A) protein hydrogels with a 2D PC embedded on the Con A protein hydrogel surface, that multivalently and selectively bind to mannan on the C. albicans cell surface to form crosslinks. The resulting crosslinks shrink the Con A protein hydrogel, reduce the 2D PC particle spacing, and blue-shift the light diffracted from the PC. The diffraction shifts can be visually monitored, measured with a spectrometer, or determined from the Debye diffraction ring diameter. Our unoptimized hydrogel sensor has a detection limit of around 32 CFU/mL for C. albicans. This sensor distinguishes between C. albicans and those microbes devoid of cell-surface mannan such as the gram-negative bacterium E. coli. This sensor provides a proof-of-concept for utilizing recognition between lectins and microbial cell surface carbohydrates to detect microorganisms in aqueous environments.

Two-dimensional photonic crystal sensors for visual detection of lectin concanavalin A.

We fabricated a two-dimensional (2-D) photonic crystal lectin sensing material that utilizes light diffraction from a 2-D colloidal array attached to the surface of a hydrogel that contains mannose carbohydrate groups. Lectin-carbohydrate interactions create hydrogel cross-links that shrink the hydrogel volume and decrease the 2-D particle spacing. This mannose containing 2-D photonic crystal sensor detects Concanavalin A (Con A) through shifts in the 2-D diffraction wavelength. Con A concentrations can be determined by measuring the diffracted wavelength or visually determined from the change in the sensor diffraction color. The concentrations are easily monitored by measuring the 2-D array Debye ring diameter. Our observed detection limit for Con A is 0.02 mg/mL (0.7 µM). The 2-D photonic crystal sensors are completely reversible and can monitor Con A solution concentration changes.

2D photonic crystal protein hydrogel coulometer for sensing serum albumin ligand binding.

Bovine and human serum albumin (BSA and HSA) are globular proteins that function as bloodstream carriers of hydrophobes such as fatty acids and drugs. We fabricated novel photonic crystal protein hydrogels by attaching 2D colloidal arrays onto pure BSA and HSA hydrogels. The wavelengths of the diffracted light sensitively report on the protein hydrogel surface area. The binding of charged species to the protein hydrogel gives rise to Donnan potentials that change the hydrogel volume causing shifts in the diffraction. These photonic crystal protein hydrogels act as sensitive Coulometers that monitor the hydrogel charge state. We find multiple high-affinity BSA and HSA binding sites for salicylate, ibuprofen and picosulfate by using these sensors to monitor binding of charged drugs. We demonstrate proof-of-concept for utilizing protein hydrogel sensors to monitor protein-ionic species binding.

Responsive ionic liquid-polymer 2D photonic crystal gas sensors.

We developed novel air-stable 2D polymerized photonic crystal (2DPC) sensing materials for visual detection of gas phase analytes such as water and ammonia by utilizing a new ionic liquid, ethylguanidine perchlorate (EGP) as the mobile phase. Because of the negligible ionic liquid vapor pressure these 2DPC sensors are indefinitely air stable and, therefore, can be used to sense atmospheric analytes. 2D arrays of ~640 nm polystyrene nanospheres were attached to the surface of crosslinked poly(hydroxyethyl methacrylate) (pHEMA)-based polymer networks dispersed in EGP. The wavelength of the bright 2D photonic crystal diffraction depends sensitively on the 2D array particle spacing. The volume phase transition response of the EGP-pHEMA system to water vapor or gaseous ammonia changes the 2DPC particle spacing, enabling the visual determination of the analyte concentration. Water absorbed by EGP increases the Flory-Huggins interaction parameter, which shrinks the polymer network and causes a blue shift in the diffracted light. Ammonia absorbed by the EGP deprotonates the pHEMA-co-acrylic acid carboxyl groups, swelling the polymer which red shifts the diffracted light.

Determination of phosphorus and potassium in commercial inorganic fertilizers by inductively coupled plasma-optical emission spectrometry: single-laboratory validation.

A two-part single-laboratory validation study was conducted for determination of the P and K content in commercial fertilizer materials by inductively coupled plasma-optical emission spectrometry (ICP-OES). While several methods exist for determination of P and K in fertilizer products, the main focus of this study was on ICP-OES determination, which offers several unique advantages. Fertilizer samples with consensus P and K values from the Magruder and Association of Fertilizer and Phosphate Chemists (AFPC) check sample programs were selected for this study. Validation materials ranging from 4.4 to 52.4% P205 (1.7 to 22.7% P) and 3 to 62% K20 (2.5 to 51.5% K) were utilized. Because all P and K compounds contained in fertilizer materials are not "available" for plants to use, this study was conducted in two parts. Part A focused on ammonium citrate-disodium EDTA as the extraction solvent, as it estimates the pool of fertilizer P and K that is considered available to plants. Part B focused on hydrochloric acid as the digestion solvent, as it estimates the total P and K content of the fertilizer product. Selectivity studies indicated that this method can have a high bias for fertilizer products containing sources of phosphite or organic P compared to gravimetric or colorimetric methods that measure just orthophosphate. Provided the analytical challenges outlined in this study are addressed, this method offers the potential for a quick, accurate, and safe alternative for determining the P and K content of commercial inorganic fertilizer materials.