Photoinduced Stitching of Self-Assembled Triangular Silver Nanoprisms at the Air-Water Interface.

This study investigates the influence of optical excitation on the self-assembly of triangular nanoprisms of silver into a continuous monolayer at the air-water interface. Langmuir monolayers of octadecylamine (ODA) have been used to electrostatically assemble citrate-capped silver triangular nanoprisms (AgTNPs) in the presence and absence of light. Under optical excitation, the nanoprisms were observed to assemble into a well-ordered monolayer through plasmon-mediated stitching, whereas the particles were merely in close contact during assembly in the dark. These findings suggest new avenues for tailoring particle properties through light-mediated assembly in two dimensions.

Recent Progress and Prospect of Metal-Organic Framework-Based Nanozymes in Biomedical Application.

A nanozyme is a nanoscale material having enzyme-like properties. It exhibits several superior properties, including low preparation cost, robust catalytic activity, and long-term storage at ambient temperatures. Moreover, high stability enables repetitive use in multiple catalytic reactions. Hence, it is considered a potential replacement for natural enzymes. Enormous research interest in nanozymes in the past two decades has made it imperative to look for better enzyme-mimicking materials for biomedical applications. Given this, research on metal-organic frameworks (MOFs) as a potential nanozyme material has gained momentum. MOFs are advanced hybrid materials made of inorganic metal ions and organic ligands. Their distinct composition, adaptable pore size, structural diversity, and ease in the tunability of physicochemical properties enable MOFs to mimic enzyme-like activities and act as promising nanozyme candidates. This review aims to discuss recent advances in the development of MOF-based nanozymes (MOF-NZs) and highlight their applications in the field of biomedicine. Firstly, different enzyme-mimetic activities exhibited by MOFs are discussed, and insights are given into various strategies to achieve them. Modification and functionalization strategies are deliberated to obtain MOF-NZs with enhanced catalytic activity. Subsequently, applications of MOF-NZs in the biosensing and therapeutics domain are discussed. Finally, the review is concluded by giving insights into the challenges encountered with MOF-NZs and possible directions to overcome them in the future. With this review, we aim to encourage consolidated efforts across enzyme engineering, nanotechnology, materials science, and biomedicine disciplines to inspire exciting innovations in this emerging yet promising field.

Cr-Detector: A simple chemosensing system for onsite Cr (VI) detection in water.

Due to the increase in urbanization and industrialization, the load of toxicants in the environment is alarming. The most common toxicants, including heavy metals and metalloids such as hexavalent Chromium, have severe pathophysiological impacts on humans and other aquatic biotas. Therefore, developing a portable rapid detection device for such toxicants in the aquatic environment is necessary. This work portrays the development of a field-portable image analysis device coupled with 3,3',5,5'-tetramethylbenzidine (TMB) as a sensing probe for chromium (VI) detection in the aquatic ecosystem. Sensor parameters, such as reagent concentration, reaction time, etc., were optimized for the sensor development and validation using a commercial UV-Vis spectrophotometer. The chemoreceptor integrated with a uniform illumination imaging system (UIIS) revealed the system's applicability toward Cr(VI) detection. The calibration curve using the R-value of image parameters allows Cr(VI) detection in the linear range of 25 to 600 ppb, which covers the prescribed permissible limit by various regulatory authorities. Furthermore, the adjusted R2 = 0.992 of the linear fit and correlation coefficients of 0.99018 against the spectrophotometric method signifies the suitability of the developed system. This TMB-coupled field-portable sensing system is the first-ever reported image analysis-based technology for detecting a wide range of Cr(VI) in aquatic ecosystems to our knowledge.

Utilising the Nanozymatic Activity of Copper-Functionalised Mesoporous C3 N5 for Sensing Biomolecules.

Designing unique nanomaterials for the selective sensing of biomolecules is of significant interest in the field of nanobiotechnology. In this work, we demonstrated the synthesis of ordered Cu nanoparticle-functionalised mesoporous C3 N5 that has unique peroxidase-like nanozymatic activity for the ultrasensitive and selective detection of glucose and glutathione. A nano hard-templating technique together with the in-situ polymerisation and self-assembly of Cu and high N-containing CN precursor was adopted to introduce mesoporosity as well as high N and Cu content in mesoporous C3 N5 . Due to the ordered structure and highly dispersed Cu in the mesoporous C3 N5 , a large enhancement of the peroxidase mimetic activity in the oxidation of a redox dye in the presence of hydrogen peroxide could be obtained. Additionally, the optimised Cu-functionalised mesoporous C3 N5 exhibited excellent sensitivity to glutathione with a low detection limit of 2.0 ppm. The strong peroxidase activity of the Cu-functionalised mesoporous C3 N5 was also effectively used for the sensing of glucose with a detection limit of 0.4 mM through glucose oxidation with glucose oxidase. This unique Cu-functionalised mesoporous C3 N5 has the potential for detecting various molecules in the environment as well as for next-generation glucose and glutathione diagnostic devices.

Repairing and Preventing Photooxidation of Few-Layer Black Phosphorus with ß-Carotene.

Few-layer black phosphorus (FLBP), a technologically important 2D material, faces a major hurdle to consumer applications: spontaneous degradation under ambient conditions. Blocking the direct exposure of FLBP to the environment has remained the key strategy to enhance its stability, but this can also limit its utility. In this paper, a more ambitious approach to handling FLBP is reported where not only is FLBP oxidation blocked, but it is also repaired postoxidation. Our approach, inspired by nature, employs the antioxidant molecule ß-carotene that protects plants against photooxidative damages to act as a protecting and repairing agent for FLBP. The mechanistic role of ß-carotene is established by a suite of spectro-microscopy techniques, in combination with computational studies and biochemical assays. Transconductance studies on FLBP-based field effect transistor (FET) devices further affirm the protective and reparative effects of ß-carotene. The outcomes indicate the potential for deploying a plethora of natural antioxidant molecules to enhance the stability of other environmentally sensitive inorganic nanomaterials and expedite their translation for technological and consumer applications.

Differential interactions of α-synuclein conformers affect refolding and activity of proteins.

The accumulation of protein aggregates as intracellular inclusions interferes with cellular protein homeostasis leading to protein aggregation diseases. Protein aggregation results in the formation of several protein conformers including oligomers and fibrils, where each conformer has its own structural characteristic and proteotoxic potential. The present study explores the effect of alpha-synuclein (α-syn) conformers on the activity and spontaneous refolding of firefly luciferase. Of the different conformers, α-syn monomers delayed the inactivation of luciferase under thermal stress conditions and enhanced the spontaneous refolding of luciferase. In contrast, the α-syn oligomers and fibrils adversely affected luciferase activity and refolding, where the oligomers inhibited spontaneous refolding, whereas a pronounced effect on the inactivation of native luciferase was observed in the case of fibrils. These results indicate that the oligomers and fibrils of α-syn interfere with the refolding of luciferase and promote its misfolding and aggregation. The study reveals the differential propensities of various conformers of a pathologically relevant protein in causing inactivation, structural modifications and misfolding of other proteins, consequently resulting in altered protein homeostasis.

Aptamer-based NanoBioSensors for seafood safety.

Chemical and biological contaminants are of primary concern in ensuring seafood safety. Rapid detection of such contaminants is needed to keep us safe from being affected. For over three decades, immunoassay (IA) technology has been used for the detection of contaminants in seafood products. However, limitations inherent to antibody generation against small molecular targets that cannot elicit an immune response, along with the instability of antibodies under ambient conditions greatly limit their wider application for developing robust detection and monitoring tools, particularly for non-biomedical applications. As an alternative, aptamer-based biosensors (aptasensors) have emerged as a powerful yet robust analytical tool for the detection of a wide range of analytes. Due to the high specificity of aptamers in recognising targets ranging from small molecules to large proteins and even whole cells, these have been suggested to be viable molecular recognition elements (MREs) in the development of new diagnostic and biosensing tools for detecting a wide range of contaminants including heavy metals, antibiotics, pesticides, pathogens and biotoxins. In this review, we discuss the recent progress made in the field of aptasensors for detection of contaminants in seafood products with a view of effectively managing their potential human health hazards. A critical outlook is also provided to facilitate translation of aptasensors from academic laboratories to the mainstream seafood industry and consumer applications.

Label-Free Electrochemiluminescence Nano-aptasensor for the Ultrasensitive Detection of ApoA1 in Human Serum.

A molybdenum sulfide/zirconium oxide/Nafion (MoS2/ZrO2/Naf) based electrochemiluminescence (ECL) aptasensor for the selective and ultrasensitive detection of ApoA1 is proposed, with Ru(bpy)3 2+ as the luminophore. The chitosan (CS) modification on the nanocomposite layer allowed glutaraldehyde (GLUT) cross-linking, resulting in the immobilization of ApoA1 aptamers. Scanning electron microscopy, tunneling electron microscopy, and energy dispersive X-ray spectroscopy were used to characterize the nanocomposite, while electrochemiluminescence (ECL), cyclic voltammetry, and electrochemical impedance spectroscopy were used to analyze the aptasensor assembly. The nanocomposite was used as an electrode modifier, which increased the intensity of the ECL signal. Due to the anionic environment produced on the sensor surface following the specific interaction of the ApoA1 biomarker with the sensor, more Ru(bpy)3 2+ were able to be electrostatically attached to the aptamer-ApoA1 complex, resulting in enhanced ECL signal. The ECL aptasensor demonstrated outstanding sensitivity for ApoA1 under optimal experimental conditions, with a detection limit of 53 fg/mL and a wide linear dynamic range of 0.1-1000 pg/mL. The potential practical applicability of this aptasensor was validated by analyzing ApoA1 in human serum samples, with recovery rates of 94-108% (n = 3). The proposed assay was found to be substantially better compared to the commercially available enzyme-linked immunosorbent assay method, as reflected from over 1500 times improvement in the detection limit for ApoA1.

Bovine and human endometrium-derived hydrogels support organoid culture from healthy and cancerous tissues.

Organoid technology has provided unique insights into human organ development, function, and diseases. Patient-derived organoids are increasingly used for drug screening, modeling rare disorders, designing regenerative therapies, and understanding disease pathogenesis. However, the use of Matrigel to grow organoids represents a major challenge in the clinical translation of organoid technology. Matrigel is a poorly defined mixture of extracellular matrix proteins and growth factors extracted from the Engelbreth-Holm-Swarm mouse tumor. The extracellular matrix is a major driver of multiple cellular processes and differs significantly between tissues as well as in healthy and disease states of the same tissue. Therefore, we envisioned that the extracellular matrix derived from a native healthy tissue would be able to support organoid growth akin to organogenesis in vivo. Here, we have developed hydrogels from decellularized human and bovine endometrium. These hydrogels supported the growth of mouse and human endometrial organoids, which was comparable to Matrigel. Organoids grown in endometrial hydrogels were proteomically more similar to the native tissue than those cultured in Matrigel. Proteomic and Raman microspectroscopy analyses showed that the method of decellularization affects the biochemical composition of hydrogels and, subsequently, their ability to support organoid growth. The amount of laminin in hydrogels correlated with the number and shape of organoids. We also demonstrated the utility of endometrial hydrogels in developing solid scaffolds for supporting high-throughput, cell culture-based applications. In summary, endometrial hydrogels overcome a major limitation of organoid technology and greatly expand the applicability of organoids to understand endometrial biology and associated pathologies.

Reactive Oxygen Species Sequestration Induced Synthesis of ß-PbO and Its Polymorphic Transformation to α-PbO at Atomically Thin Regimes.

The emergence of attractive properties in materials at atomically thin regimes has seen an ongoing interest in two-dimensional (2D) materials. An aspect that has lacked focused attention is the effect of 2D material thickness on its crystal structure. As several layered materials naturally exist in mixed metastable phases, it raises an important question of whether a specific polymorph of these mixed-phase materials will be favored at atomically thin limits. This work attempts to address this issue by employing lead monoxide as a model 2D polymorphic system. We propose a reactive oxygen species (ROS) sequestration-mediated liquid-phase exfoliation (LPE) strategy for the facile synthesis of ultrathin PbO. This is followed by a suite of microscopic and spectroscopic analyses of the PbO nanosheets that reveals the polymorphic transformation of orthorhombic (ß) PbO to its tetragonal (α) analogue with reduction in nanosheet thickness. The transformation process reveals an interesting crystal structure of ultrathin 2D PbO where [001]-oriented domains of α-PbO coexist alongside [100]-oriented regions of ß-PbO. Density functional theory (DFT) calculations support our experimental data by revealing a higher thermodynamic stability of the tetragonal phase in PbO monolayers. These findings are likely to instigate interest in carefully evaluating the crystal structures of ultrathin 2D materials while promoting research in understanding the phase transformation across a range of 2D crystals.

Bimetallic nanozyme mediated urine glucose monitoring through discriminant analysis of colorimetric signal.

The ability to detect glucose concentrations in human urine offers a non-invasive approach to monitor changes in blood glucose, kidney health and vascular complications associated with diabetes. We show the potential of employing catalytically active nanoparticles directly grown on textiles to produce a dose-dependent colorimetric sensor for glucose. We use a galvanic replacement (GR) reaction for the synthesis of bimetallic nanoparticles. Here, Cu nanoparticles act as a sacrificial template that undergoes a spontaneous electroless GR reaction when exposed to metal ions of gold, silver, platinum, and palladium to form bimetallic Cu-M nanoparticles (M = Au, Ag, Pt, or Pd). The evaluation of their intrinsic peroxidase-mimicking catalytic activity ("nanozyme") in comparison to that of the Cu nanozyme revealed that the bimetallic systems show a higher catalytic rate with the Cu-Pt nanozyme showing the highest catalytic efficiency. This property of the Cu-Pt nanozyme was then utilized to detect glucose in human urine using the glucose oxidase enzyme as a molecular recognition element. A key outcome of our study is the ability to detect urine glucose without requiring sample dilution which is an advantage over the gold standard GOx-POx method and significantly more reliable performance over commercial urine glucose dipsticks. The difference in the intensity of the colorimetric response between different glucose concentrations further allowed this sensor system to be combined with digital imaging tools for multivariate analysis.

Tuning the enzyme-like activities of cerium oxide nanoparticles using a triethyl phosphite ligand.

Cerium oxide nanoparticles (CeNPs) exhibit excellent in vitro and in vivo antioxidant properties, determined by the redox switching of surface cerium ions between their two oxidation states (Ce3+ and Ce4+). It is known that ligands such as triethyl phosphite (TEP) can tune the redox behavior of CeNPs and change their biological enzyme-mimetic activities; however, the corresponding mechanism for such a behavior is completely unknown. Herein, we have studied the effect of TEP in promoting the SOD-enzyme-like activity in CeNPs with high and low Ce3+/Ce4+ ratio, which were synthesized by wet chemical and thermal hydrolysis methods, respectively, and incubated with varying concentrations of TEP. X-ray diffraction, UV-visible, photoluminescence, X-ray photoelectron spectroscopy, and Raman spectroscopy combined with DFT calculations were used to investigate the interaction of TEP on the surface of CeNPs. We observed a clear correlation between TEP concentration and the formation of surface oxygen vacancies. XPS analysis confirmed the increase in Ce3+ concentration after interaction with TEP. Moreover, we show that TEP's influence depends on the surface Ce3+/Ce4+ ratio. The superoxide dismutase-, catalase-, and oxidase-like activities of CeNPs with high Ce3+/Ce4+ ratio are not affected by TEP interaction, whereas catalase- and oxidase-like activities of CeNPs with low Ce3+/Ce4+ ratio decrease and the SOD-like activity is found to increase upon incubation with different concentrations of TEP. We also demonstrate that TEP interaction does not affect the regeneration of the CeNP surface, while the DFT calculations show that TEP facilitates the formation of defects on the surface of stoichiometric cerium oxide by reducing the oxygen vacancy formation energy. CeNPs with low Ce3+/Ce4+ ratio incubated with TEP also exhibited good antibacterial activity as compared to the CeNPs or TEP alone.

Classification of COVID-19 from chest x-ray images using deep features and correlation coefficient.

COVID-19 is a viral disease that in the form of a pandemic has spread in the entire world, causing a severe impact on people's well being. In fighting against this deadly disease, a pivotal step can prove to be an effective screening and diagnosing step to treat infected patients. This can be made possible through the use of chest X-ray images. Early detection using the chest X-ray images can prove to be a key solution in fighting COVID-19. Many computer-aided diagnostic (CAD) techniques have sprung up to aid radiologists and provide them a secondary suggestion for the same. In this study, we have proposed the notion of Pearson Correlation Coefficient (PCC) along with variance thresholding to optimally reduce the feature space of extracted features from the conventional deep learning architectures, ResNet152 and GoogLeNet. Further, these features are classified using machine learning (ML) predictive classifiers for multi-class classification among COVID-19, Pneumonia and Normal. The proposed model is validated and tested on publicly available COVID-19 and Pneumonia and Normal dataset containing an extensive set of 768 images of COVID-19 with 5216 training images of Pneumonia and Normal patients. Experimental results reveal that the proposed model outperforms other previous related works. While the achieved results are encouraging, further analysis on the COVID-19 images can prove to be more reliable for effective classification.

Excess iron promotes emergence of foamy macrophages that overexpress ferritin in the lungs of silicosis patients.

BACKGROUND AND OBJECTIVE: Inhalation of high concentrations of respirable crystalline silica (RCS) can lead to silicosis. RCS contains varying levels of iron, which can cause oxidative stress and stimulate ferritin production. This study evaluated iron-related and inflammatory markers in control and silicosis patients. METHODS: A cohort of stone benchtop industry workers (n = 18) were radiologically classified by disease severity into simple or complicated silicosis. Peripheral blood and bronchoalveolar lavage (BAL) were collected to measure iron, ferritin, C-reactive protein, serum amyloid A and serum silicon levels. Ferritin subunit expression in BAL and transbronchial biopsies was analysed by reverse transcription quantitative PCR. Lipid accumulation in BAL macrophages was assessed by Oil Red O staining. RESULTS: Serum iron levels were significantly elevated in patients with silicosis, with a strong positive association with serum ferritin levels. In contrast, markers of systemic inflammation were not increased in silicosis patients. Serum silicon levels were significantly elevated in complicated disease. BAL macrophages from silicosis patients were morphologically consistent with lipid-laden foamy macrophages. Ferritin light chain (FTL) mRNA expression in BAL macrophages was also significantly elevated in simple silicosis patients and correlated with systemic ferritin. CONCLUSION: Our findings suggest that elevated iron levels during the early phases of silicosis increase FTL expression in BAL macrophages, which drives elevated BAL and serum ferritin levels. Excess iron and ferritin were also associated with the emergence of a foamy BAL macrophage phenotype. Ferritin may represent an early disease marker for silicosis, where increased levels are independent of inflammation and may contribute to fibrotic lung remodelling.

Functionalized Concave Cube Gold Nanoparticles as Potent Antimicrobial Agents against Pathogenic Bacteria.

Gold (Au) is an inert metal in a bulk state; however, it can be used for the preparation of Au nanoparticles (i.e., AuNPs) for multidimensional applications in the field of nanomedicine and nanobiotechnology. Herein, monodisperse concave cube AuNPs (CCAuNPs) were synthesized and functionalized with a natural antioxidant lipoic acid (LA) and a tripeptide glutathione (GSH) because different crystal facets of AuNPs provide binding sites for distinct ligands. There was an ∼10 nm bathochromic shift of the UV-vis spectrum when CCAuNPs were functionalized with LA, and the size of the as-synthesized monodisperse CCAu nanoparticles was 76 nm. The LA-functionalized CCAu nanoparticles (i.e., CCAuLA) showed the highest antibacterial activity against Bacillus subtilis. Both fluorescence images and scanning electron microscopy images confirm the damage of the bacterial cell wall as the mode of antibacterial activity of CCAuNPs. CCAuNPs also cause the oxidation of bacterial cell membrane fatty acids to produce reactive oxygen species, which pave the way for the death of bacteria. Both CCAu nanoparticles and their functionalized derivatives showed excellent hemocompatibility (i.e., percentage of hemolysis is <5% at 80 µg of AuNPs) to human red blood cells and very high biocompatibility to HeLa, L929, and Chinese hamster ovary-green fluorescent protein (CHO-GFP) cells. Taken together, LA and GSH enhance the antibacterial activity and biocompatibility, respectively, of CCAu nanoparticles that interact with the bacteria through Coulomb as well as hydrophobic interactions before demonstrating antibacterial propensity.

Computational Intelligence Enabled Student Performance Estimation in the Age of COVID-19.

The sudden advent of COVID-19 pandemic left educational institutions in a difficult situation for the semester evaluation of students; especially where the online participation was difficult for the students. Such a situation may also happen during a similar disaster in the future. Through this work, we want to study the question: can the deep learning methods be leveraged to predict student grades based on the available performance of students. To this end, this paper presents an in-depth analysis of deep learning and machine learning approaches for the formulation of an automated students' performance estimation system that works on partially available students' academic records. Our main contributions are: (a) a large dataset with 15 courses (shared publicly for academic research); (b) statistical analysis and ablations on the estimation problem for this dataset; (c) predictive analysis through deep learning approaches and comparison with other arts and machine learning algorithms. Unlike previous approaches that rely on feature engineering or logical function deduction, our approach is fully data-driven and thus highly generic with better performance across different prediction tasks. The main takeaways from this study are: (a) for better prediction rates, it is desirable to have multiple low weightage tests than few very high weightage exams; (b) the latent space models are better estimators than sequential models; (c) deep learning models have the potential to very accurately estimate the student performance and their accuracy only improves as the training data are increased.

Erratum: Hussain et al. Increased Crystallization of CuTCNQ in Water/DMSO Bisolvent for Enhanced Redox Catalysis. Nanomaterials 2021, 11, 954.

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AI-based diagnosis of COVID-19 patients using X-ray scans with stochastic ensemble of CNNs.

According to the World Health Organization (WHO), novel coronavirus (COVID-19) is an infectious disease and has a significant social and economic impact. The main challenge in fighting against this disease is its scale. Due to the outbreak, medical facilities are under pressure due to case numbers. A quick diagnosis system is required to address these challenges. To this end, a stochastic deep learning model is proposed. The main idea is to constrain the deep-representations over a Gaussian prior to reinforce the discriminability in feature space. The model can work on chest X-ray or CT-scan images. It provides a fast diagnosis of COVID-19 and can scale seamlessly. The work presents a comprehensive evaluation of previously proposed approaches for X-ray based disease diagnosis. The approach works by learning a latent space over X-ray image distribution from the ensemble of state-of-the-art convolutional-nets, and then linearly regressing the predictions from an ensemble of classifiers which take the latent vector as input. We experimented with publicly available datasets having three classes: COVID-19, normal and pneumonia yielding an overall accuracy and AUC of 0.91 and 0.97, respectively. Moreover, for robust evaluation, experiments were performed on a large chest X-ray dataset to classify among Atelectasis, Effusion, Infiltration, Nodule, and Pneumonia classes. The results demonstrate that the proposed model has better understanding of the X-ray images which make the network more generic to be later used with other domains of medical image analysis.

Copper Tetracyanoquinodimethane (CuTCNQ): A Metal-Organic Semiconductor for Room-Temperature Visible to Long-Wave Infrared Photodetection.

Mid-wave and long-wave infrared (MWIR and LWIR) detection play vital roles in applications that include health care, remote sensing, and thermal imaging. However, detectors in this spectral range often require complex fabrication processes and/or cryogenic cooling and are typically expensive, which motivates the development of simple alternatives. Here, we demonstrate broadband (0.43-10 µm) room-temperature photodetection based on copper tetracyanoquinodimethane (CuTCNQ), a metal-organic semiconductor, synthesized via a facile wet-chemical reaction. The CuTCNQ crystals are simply drop-cast onto interdigitated electrode chips to realize photoconductors. The photoresponse is governed by a combination of interband (0.43-3.35 µm) and midgap (3.35-10 µm) transitions. The devices show response times (∼365 µs) that would be sufficient for many infrared applications (e.g., video rate imaging), with a frequency cutoff point of 1 kHz.

L-Cysteine as an Irreversible Inhibitor of the Peroxidase-Mimic Catalytic Activity of 2-Dimensional Ni-Based Nanozymes.

The ability to modulate the catalytic activity of inorganic nanozymes is of high interest. In particular, understanding the interactions of inhibitor molecules with nanozymes can bring them one step closer to the natural enzymes and has thus started to attract intense interest. To date, a few reversible inhibitors of the nanozyme activity have been reported. However, there are no reports of irreversible inhibitor molecules that can permanently inhibit the activity of nanozymes. In the current work, we show the ability of L-cysteine to act as an irreversible inhibitor to permanently block the nanozyme activity of 2-dimensional (2D) NiO nanosheets. Determination of the steady state kinetic parameters allowed us to obtain mechanistic insights into the catalytic inhibition process. Further, based on the irreversible catalytic inhibition capability of L-cysteine, we demonstrate a highly specific sensor for the detection of this biologically important molecule.