Keeping Analytical Chemistry Training Up-to-Date.

The undergraduate analytical chemistry curriculum serves to equip students with the knowledge and skills for work outside of classroom training. As such, instructors face a challenging task in deciding the breadth and depth of topics for their courses to ensure their syllabi can remain up-to-date with today's needs. We propose that instructors consider covering capillary electrophoresis (CE) and lab-on-a-chip (LOC) technologies in their analytical chemistry courses. Past surveys of the curriculum show a noticeable lack of emphasis on these topics, which we feel is a missed opportunity and one that holds potential for the collective benefit of instructors and students. CE and LOCs are utilized in a diverse array of fields like biochemistry, pharmaceutical production, materials science, and environmental analysis, and their applications are becoming increasingly important amidst the growing movement toward environmentally sustainable practices and green chemistry. They are also more accessible in the analytical chemistry classroom compared with typical benchtop instruments due to the flexibility of their size and cost. This makes them easier to obtain, maintain, and transport for use and demonstration purposes. Additionally, interwoven in these topics are core concepts that are fundamental to analytical chemistry; thus, covering them will inherently reinforce students' understanding of fundamental knowledge. Therefore, we believe increased coverage of CE and LOCs can better prepare undergraduates for modern analytical chemistry work in various industries and fields of research.

Ratiometric Fluorescence Aptasensor of Allergen Protein Based on Multivalent Aptamer-Encoded DNA Flowers as Fluorescence Resonance Energy Transfer Platform.

Life-threatening allergic reactions to food allergens, particularly peanut protein Ara h1, are a growing public health concern affecting millions of people worldwide. Thus, accurate and rapid detection is necessary for allergen labeling and dietary guidance and ultimately preventing allergic incidents. Herein, we present a novel ratiometric fluorescence aptasensor based on multivalent aptamer-encoded DNA flowers (Mul-DNFs) for the high-stability and sensitive detection of allergen Ara h1. The flower-shaped Mul-DNFs were spontaneously packaged using ultralong polymeric DNA amplicons driven by a rolling circle amplification reaction, which contains a large number of Ara h1 specific recognition units and has excellent binding properties. Furthermore, dual-color fluorescence-labeled Mul-DNFs probes were developed by hybridizing them with Cy3- and Cy5-labeled complementary DNA (cDNA) to serve as a ratiometric fluorescence aptasensor platform based on fluorescence resonance energy transfer. Benefiting from the combined merits of the extraordinary synergistic multivalent binding ability of Mul-DNFs, the excellent specificity of the aptamer, and the sensitivity of the ratiometric sensor to avoid exogenous interference. The developed ratiometric aptasensor showed excellent linearity (0.05-2000 ng mL-1) with a limit of detection of 0.02 ng mL-1. Additionally, the developed ratiometric fluorescence aptasensor was utilized for quantifying the presence of Ara h1 in milk, infant milk powder, cookies, bread, and chocolate with recoveries of 95.7-106.3%. The proposed ratiometric aptasensor is expected to be a prospective universal aptasensor platform for the rapid, sensitive, and accurate determination of food and environmental hazards.

Averaging Strategy for Interpretable Machine Learning on Small Datasets to Understand Element Uptake after Seed Nanotreatment.

Understanding plant uptake and translocation of nanomaterials is crucial for ensuring the successful and sustainable applications of seed nanotreatment. Here, we collect a dataset with 280 instances from experiments for predicting the relative metal/metalloid concentration (RMC) in maize seedlings after seed priming by various metal and metalloid oxide nanoparticles. To obtain unbiased predictions and explanations on small datasets, we present an averaging strategy and add a dimension for interpretable machine learning. The findings in post-hoc interpretations of sophisticated LightGBM models demonstrate that solubility is highly correlated with model performance. Surface area, concentration, zeta potential, and hydrodynamic diameter of nanoparticles and seedling part and relative weight of plants are dominant factors affecting RMC, and their effects and interactions are explained. Furthermore, self-interpretable models using the RuleFit algorithm are established to successfully predict RMC only based on six important features identified by post-hoc explanations. We then develop a visualization tool called RuleGrid to depict feature effects and interactions in numerous generated rules. Consistent parameter-RMC relationships are obtained by different methods. This study offers a promising interpretable data-driven approach to expand the knowledge of nanoparticle fate in plants and may profoundly contribute to the safety-by-design of nanomaterials in agricultural and environmental applications.

Auranofin inhibits virulence pathways in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is widely attributed as the leading cause of hospital-acquired infections. Due to intrinsic antibiotic resistance mechanisms and the ability to form biofilms, P. aeruginosa infections are challenging to treat. P. aeruginosa employs multiple virulence mechanisms to establish infections, many of which are controlled by the global virulence regulator Vfr. An attractive strategy to combat P. aeruginosa infections is thus the use of anti-virulence compounds. Here, we report the discovery that FDA-approved drug auranofin attenuates virulence pathways in P. aeruginosa, including quorum sensing (QS) and Type IV pili (TFP). We show that auranofin acts via multiple targets, one of which being Vfr. Consistent with inhibition of QS and TFP expression, we show that auranofin attenuates biofilm maturation, and when used in combination with colistin, displays strong synergy in eradicating P. aeruginosa biofilms. Auranofin may have immediate applications as an anti-virulence drug against P. aeruginosa infections.

General and robust covalently linked graphene oxide affinity grids for high-resolution cryo-EM.

Affinity grids have great potential to facilitate rapid preparation of even quite impure samples in single-particle cryo-electron microscopy (EM). Yet despite the promising advances of affinity grids over the past decades, no single strategy has demonstrated general utility. Here we chemically functionalize cryo-EM grids coated with mostly one or two layers of graphene oxide to facilitate affinity capture. The protein of interest is tagged using a system that rapidly forms a highly specific covalent bond to its cognate catcher linked to the grid via a polyethylene glycol (PEG) spacer. Importantly, the spacer keeps particles away from both the air-water interface and the graphene oxide surface, protecting them from potential denaturation and rendering them sufficiently flexible to avoid preferential sample orientation concerns. Furthermore, the PEG spacer successfully reduces nonspecific binding, enabling high-resolution reconstructions from a much cruder lysate sample.

Simultaneous Polar Metabolite and N-Glycan Extraction Workflow for Joint-Omics Analysis: A Synergistic Approach for Novel Insights into Diseases.

Bioinformatics and machine learning tools have made it possible to integrate data across different -omics platforms for novel multiomic insights into diseases. To synergistically process -omics data in an integrative manner, analyte extractions for each -omics type need to be done on the same set of clinical samples. Therefore, we introduce a simultaneous dual extraction method for generating both metabolomic (polar metabolites only) and glycomic (protein-derived N-glycans only) profiles from one sample with good extraction efficiency and reproducibility. As proof of the usefulness of the extraction and joint-omics workflow, we applied it on platelet samples obtained from a cohort study comprising 66 coronary heart disease (CHD) patients and 34 matched healthy community-dwelling controls. The metabolomics and N-glycomics data sets were subjected to block partial least-squares-discriminant analysis (block-PLS-DA) based on sparse generalized canonical correlation analysis (CCA) for identifying relevant mechanistic interactions between metabolites and glycans. This joint-omics investigation revealed intermodulative roles that protein-bound carbohydrates or glycoproteins and amino acids have in metabolic pathways and through intermediate protein dysregulations. It also suggested a protective role of the glyco-redox network in CHD, demonstrating proof-of-principle for a joint-omics analysis in providing new insights into disease mechanisms, as enabled by a simultaneous polar metabolite and protein-derived N-glycan extraction workflow.

N-glycan profiles of acute myocardial infarction patients reveal potential biomarkers for diagnosis, severity assessment and treatment monitoring.

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Diagnostic challenges remain in this highly time-sensitive condition. Using capillary electrophoresis-laser-induced fluorescence, we analyzed the blood plasma N-glycan profile in a cohort study comprising 103 patients with AMI and 69 controls. Subsequently, the data generated was subjected to classification modeling to identify potential AMI biomarkers. An area under the Receiving Operating Characteristic curve (AUCROC) of 0.81 was obtained when discriminating AMI vs. non-MI patients. We postulate that the glycan profile involves a switch from a pro- to an anti-inflammatory state in the AMI pathophysiology. This was supported by significantly decreased levels in galactosylation, alongside increased levels in sialylation, afucosylation and GlcNAc bisection levels in the blood plasma of AMI patients. By substantiating the glycomics analysis with immunoglobulin G (IgG) protein measurements, robustness of the glycan-based classifiers was demonstrated. Changes in AMI-related IgG activities were also confirmed to be associated with alterations at the glycosylation level. Additionally, a glycan-biomarker panel derived from glycan features and current clinical biomarkers performed remarkably (AUCROC = 0.90, sensitivity = 0.579 at 5% false positive rate) when discriminating between patients with ST-segment elevation MI (n = 84) and non-ST-segment elevation MI (n = 19). Moreover, by applying the model trained using glycomics information, AMI and controls can still be discriminated at 1 and 6 months after baseline. Thus, glycomics biomarkers could potentially serve as a valuable complementary test to current diagnostic biomarkers. Additional research on their utility and associated biomechanisms via a large-scale study is recommended.

Co-Localization of Gastrointestinal Stromal Tumors (GIST) and Peritoneal Mesothelioma: A Case Series.

PURPOSE: Gastrointestinal stromal tumor (GIST) is associated with increased risk of additional cancers. In this study, synchronous GIST, and peritoneal mesothelioma (PM) were characterized to evaluate the relationship between these two cancers. METHODS: A retrospective chart review was conducted for patients diagnosed with both GIST and PM between July 2010 and June 2021. Patient demographics, past tumor history, intraoperative reports, cross-sectional imaging, peritoneal cancer index (PCI) scoring, somatic next-generation sequencing (NGS) analysis, and histology were reviewed. RESULTS: Of 137 patients who underwent primary GIST resection from July 2010 to June 2021, 8 (5.8%) were found to have synchronous PM, and 4 patients (50%) had additional cancers and/or benign tumors. Five (62.5%) were male, and the median age at GIST diagnosis was 57 years (range: 45-76). Seventy-five percent of GISTs originated from the stomach. Of the eight patients, one patient had synchronous malignant mesothelioma (MM), and the remaining had well-differentiated papillary mesothelioma (WDPM), which were primarily located in the region of the primary GIST (89%). The median PCI score was 2 in the WDPM patients. NGS of GIST revealed oncogenic KIT exon 11 (62.5%), PDGFRA D842V (25%), or SDH (12.5%) mutations, while NGS of the MM revealed BAP1 and PBRM1 alterations. CONCLUSIONS: One in 17 GIST patients undergoing resection in this series have PM, which is significantly higher than expected if these two diseases were considered as independent events. Our results indicate that synchronous co-occurrence of GIST and PM is an underrecognized finding, suggesting a possible relationship that deserves further investigation.

TomoAlign: A novel approach to correcting sample motion and 3D CTF in CryoET.

TomoAlign is a software package that integrates tools to mitigate two important resolution limiting factors in cryoET, namely the beam-induced sample motion and the contrast transfer function (CTF) of the microscope. The package is especially focused on cryoET of thick specimens where fiducial markers are required for accurate tilt-series alignment and sample motion estimation. TomoAlign models the beam-induced sample motion undergone during the tilt-series acquisition. The motion models are used to produce motion-corrected subtilt-series centered on the particles of interest. In addition, the defocus of each particle at each tilt image is determined and can be corrected, resulting in motion-corrected and CTF-corrected subtilt-series from which the subtomograms can be computed. Alternatively, the CTF information can be passed on so that CTF correction can be carried out entirely within external packages like Relion. TomoAlign serves as a versatile tool that can streamline the cryoET workflow from initial alignment of tilt-series to final subtomogram averaging during in situ structure determination.

Evaluation of Anti-Inflammatory Effects of Celery Leaf and Stem Extracts in LPS-Induced RAW 264.7 Cells Using Nitric Oxide Assay and LC-MS Based Metabolomics.

The present work demonstrated and compared the anti-inflammatory effects of celery leaf (CLE) and stem (CSE) extracts. LC-MS-based metabolomics were an effective approach to achieve the biomarker identification and pathway elucidation associated with the reduction in inflammatory responses. The celery extracts suppressed LPS-induced NO production in RAW 264.7 cells, and CLE was five times more effective than CSE. Distinct differences were revealed between the control and celery-treated samples among the 24 characteristic metabolites that were identified. In celery-treated LPS cells, reversals of intracellular (citrulline, proline, creatine) and extracellular (citrulline, lysine) metabolites revealed that the therapeutic outcomes were closely linked to arginine metabolism. Reversals of metabolites when treated with CLE (aspartate, proline) indicated targeted effects on the TCA and urea cycles, while, in the case of CSE (histidine, glucose), the glycolysis and the pentose phosphate pathways were implicated. Subsequently, apigenin and bergapten in CLE were identified as potential biomarkers mediating the anti-inflammatory response.

Gut microbiota from high-risk men who have sex with men drive immune activation in gnotobiotic mice and in vitro HIV infection.

Men who have sex with men (MSM) have differences in immune activation and gut microbiome composition compared with men who have sex with women (MSW), even in the absence of HIV infection. Gut microbiome differences associated with HIV itself when controlling for MSM, as assessed by 16S rRNA sequencing, are relatively subtle. Understanding whether gut microbiome composition impacts immune activation in HIV-negative and HIV-positive MSM has important implications since immune activation has been associated with HIV acquisition risk and disease progression. To investigate the effects of MSM and HIV-associated gut microbiota on immune activation, we transplanted feces from HIV-negative MSW, HIV-negative MSM, and HIV-positive untreated MSM to gnotobiotic mice. Following transplant, 16S rRNA gene sequencing determined that the microbiomes of MSM and MSW maintained distinct compositions in mice and that specific microbial differences between MSM and MSW were replicated. Immunologically, HIV-negative MSM donors had higher frequencies of blood CD38+ HLADR+ and CD103+ T cells and their fecal recipients had higher frequencies of gut CD69+ and CD103+ T cells, compared with HIV-negative MSW donors and recipients, respectively. Significant microbiome differences were not detected between HIV-negative and HIV-positive MSM in this small donor cohort, and immune differences between their recipients were trending but not statistically significant. A larger donor cohort may therefore be needed to detect immune-modulating microbes associated with HIV. To investigate whether our findings in mice could have implications for HIV replication, we infected primary human lamina propria cells stimulated with isolated fecal microbiota, and found that microbiota from MSM stimulated higher frequencies of HIV-infected cells than microbiota from MSW. Finally, we identified several microbes that correlated with immune readouts in both fecal recipients and donors, and with in vitro HIV infection, which suggests a role for gut microbiota in immune activation and potentially HIV acquisition in MSM.

Virtual Reality or Augmented Reality as a Tool for Studying Bystander Behaviors in Interpersonal Violence: Scoping Review.

BACKGROUND: To provide participants with a more real and immersive intervening experience, virtual reality (VR) and/or augmented reality (AR) technologies have been integrated into some bystander intervention training programs and studies measuring bystander behaviors. OBJECTIVE: We focused on whether VR or AR can be used as a tool to enhance training bystanders. We reviewed the evidence from empirical studies that used VR and/or AR as a tool for examining bystander behaviors in the domain of interpersonal violence research. METHODS: Two librarians searched for articles in databases, including APA PsycInfo (Ovid), Criminal Justice Abstracts (EBSCO), Medline (Ovid), Applied Social Sciences Index & Abstracts (ProQuest), Sociological Abstracts (ProQuest), and Scopus till April 15, 2020. Studies focusing on bystander behaviors in conflict situations were included. All study types (except reviews) written in English in any discipline were included. RESULTS: The search resulted in 12,972 articles from six databases, and the articles were imported into Covidence. Eleven studies met the inclusion and exclusion criteria. All 11 articles examined the use of VR as a tool for studying bystander behaviors. Most of the studies were conducted in US young adults. The types of interpersonal violence were school bullying, dating violence, sexual violence/assault, and soccer-associated violence. VR technology was used as an observational measure and bystander intervention program. We evaluated the different uses of VR for bystander behaviors and noted a lack of empirical evidence for AR as a tool. We also discuss the empirical evidence regarding the design, effectiveness, and limitations of implementing VR as a tool in the reviewed studies. CONCLUSIONS: The reviewed results have implications and recommendations for future research in designing and implementing VR/AR technology in the area of interpersonal violence. Future studies in this area may further contribute to the use of VR as an observational measure and explore the potential use of AR to study bystander behaviors.

Amino and PEG-amino graphene oxide grids enrich and protect samples for high-resolution single particle cryo-electron microscopy.

Cryo-EM samples prepared using traditional methods often suffer from too few particles, poor particle distribution, strongly biased orientation, or damage from the air-water interface. Here we report that functionalization of graphene oxide (GO) coated grids with amino groups concentrates samples on the grid with improved distribution and orientation. By introducing a PEG spacer, particles are kept away from both the GO surface and the air-water interface, protecting them from potential denaturation.

A label-free lead(II) ion sensor based on surface plasmon resonance and DNAzyme-gold nanoparticle conjugates.

Detection of lead(II) (Pb2+) ions in water is important for the protection of human health and environment. The growing demand for onsite detection still faces challenges for sensitive and easy-to-use methods. In this work, a novel surface plasmon resonance (SPR) biosensor based on GR-5 DNAzyme and gold nanoparticles (AuNPs) was developed. Thiolated DNAzyme was immobilized on the gold surface of the sensor chip followed by anchoring the substrate-functionalized AuNPs through the DNAzyme-substrate hybridization. The coupling between the localized surface plasmon (LSP) of AuNPs and the surface plasmon polaritons (SPP) on the gold sensor surface was used to improve the sensitivity. The substrate cleavage in the presence of Pb2+ ions was catalyzed by DNAzyme, leading to the removal of AuNPs and the diminished LSP-SPP coupling. The optimal detection limit was 80 pM for the sensor fabricated with 1 µM DNAzyme, corresponding to two or three orders of magnitude lower than the toxicity levels of Pb2+ in drinking water defined by WHO and USEPA. By tuning the surface coverage of DNAzyme, the sensitivity and dynamic range could be controlled. This sensor also featured high selectivity to Pb2+ ions and simple detection procedure. Successful detection of Pb2+ ions in groundwater indicates that this method has the prospect in the onsite detection of Pb2+ ions in water. Given the variety of AuNPs and metal-specific DNAzymes, this detection strategy would lead to the development of more sensitive and versatile heavy metal sensors. Graphical abstract.

Consideration of sample motion in cryo-tomography based on alignment residual interpolation.

Recently, it has been shown that the resolution in cryo-tomography could be improved by considering the sample motion in tilt-series alignment and reconstruction, where a set of quadratic polynomials were used to model this motion. One requirement of this polynomial method is the optimization of a large number of parameters, which may limit its practical applicability. In this work, we propose an alternative method for modeling the sample motion. Starting from the standard fiducial-based tilt-series alignment, the method uses the alignment residual as local estimates of the sample motion at the 3D fiducial positions. Then, a scattered data interpolation technique characterized by its smoothness and a closed-form solution is applied to model the sample motion. The motion model is then integrated in the tomographic reconstruction. The new method improves the tomogram quality similar to the polynomial one, with the important advantage that the determination of the motion model is greatly simplified, thereby overcoming one of the major limitations of the polynomial model. Therefore, the new method is expected to make the beam-induced motion correction methodology more accessible to the cryoET community.

Toxicity assessment of copper by electrochemically active bacteria in wastewater.

A bioelectrochemical sensor (BES) was constructed for toxicity assessment of copper in contaminated domestic sewage. Electrochemically active bacteria (EAB), whose growth was supported by the bioenergy generated from an in situ metallurgical process, functioned as the sensing elements. The external resistance of metallurgical BES was optimized based on linear sweep voltammetry analysis. The stabilized BES was utilized to monitor the copper toxicity in real wastewater. During the less than 1-h sensing period, copper concentration ranging from 1 to 5 mg L-1 could be detected. A power output of around 100 Wh (kg Cu)-1 and metallic copper resource were obtained simultaneously. This study demonstrated that the highly active EAB species enriched in metallurgical BES could be a promising candidate for rapid and reliable evaluation of copper toxicity in real domestic wastewater.

Cryo-tomography tilt-series alignment with consideration of the beam-induced sample motion.

Recent evidence suggests that the beam-induced motion of the sample during tilt-series acquisition is a major resolution-limiting factor in electron cryo-tomography (cryoET). It causes suboptimal tilt-series alignment and thus deterioration of the reconstruction quality. Here we present a novel approach to tilt-series alignment and tomographic reconstruction that considers the beam-induced sample motion through the tilt-series. It extends the standard fiducial-based alignment approach in cryoET by introducing quadratic polynomials to model the sample motion. The model can be used during reconstruction to yield a motion-compensated tomogram. We evaluated our method on various datasets with different sample sizes. The results demonstrate that our method could be a useful tool to improve the quality of tomograms and the resolution in cryoET.

A simple and robust procedure for preparing graphene-oxide cryo-EM grids.

Graphene oxide (GO) sheets have been used successfully as a supporting substrate film in several recent cryogenic electron-microscopy (cryo-EM) studies of challenging biological macromolecules. However, difficulties in preparing GO-covered holey carbon EM grids have limited their widespread use. Here, we report a simple and robust method for covering holey carbon EM grids with GO sheets and demonstrate that these grids can be used for high-resolution single particle cryo-EM. GO substrates adhere macromolecules, allowing cryo-EM grid preparation with lower specimen concentrations and provide partial protection from the air-water interface. Additionally, the signal of the GO lattice beneath the frozen-hydrated specimen can be discerned in many motion-corrected micrographs, providing a high-resolution fiducial for evaluating beam-induced motion correction.

Multiplexing N-glycan analysis by DNA analyzer.

Analysis of N-glycan structures has been gaining attentions over the years due to their critical importance to biopharma-based applications and growing roles in biological research. Glycan profiling is also critical to the development of biosimilar drugs. The detailed characterization of N-glycosylation is mandatory because it is a nontemplate driven process and that significantly influences critical properties such as bio-safety and bio-activity. The ability to comprehensively characterize highly complex mixtures of N-glycans has been analytically challenging and stimulating because of the difficulties in both the structure complexity and time-consuming sample pretreatment procedures. CE-LIF is one of the typical techniques for N-glycan analysis due to its high separation efficiency. In this paper, a 16-capillary DNA analyzer was coupled with a magnetic bead glycan purification method to accelerate the sample preparation procedure and therefore increase N-glycan assay throughput. Routinely, the labeling dye used for CE-LIF is 8-aminopyrene-1,3,6-trisulfonic acid, while the typical identification method involves matching migration times with database entries. Two new fluorescent dyes were used to either cross-validate and increase the glycan identification precision or simplify sample preparation steps. Exoglycosidase studies were carried out using neuramididase, galactosidase, and fucosidase to confirm the results of three dye cross-validation. The optimized method combines the parallel separation capacity of multiple-capillary separation with three labeling dyes, magnetic bead assisted preparation, and exoglycosidase treatment to allow rapid and accurate analysis of N-glycans. These new methods provided enough useful structural information to permit N-glycan structure elucidation with only one sample injection.