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Gestational diabetes mellitus (GDM) is a pathological condition of glucose intolerance associated with adverse pregnancy outcomes and increased risk of developing maternal type 2 diabetes later in life. Metabolomics is finding increasing use in the study of GDM. To date, GDM-specific metabolomic changes have not been completely elucidated.In this pilot study, metabolomics fingerprinting data, obtained by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF-MS), of 54 healthy pregnant women and 49 patients with GDM at the second and third gestational trimesters were analyzed. Multilevel statistical methods were used to process complex metabolomic data from the retrospective cohorts.Using univariate analysis (p 0.05), 41 metabolites were identified as having the most significant differences between these two groups. Lipid metabolites, particularly glycerophospholipids, were the most prevalent class of altered compounds. In addition, metabolites with previously unknown connection to GDM - such as monoacylglycerol, dihydrobiopterin, and 13S-hydroxyoctadecadienoic acid - were identified with strong discriminative power. The main metabolic pathways affected by GDM included glycerophospholipid metabolism, linoleic acid metabolism, and D-arginine and D-ornithine metabolism.Our data provide a comprehensive overview of metabolite changes at different stages of pregnancy, which offers further insights into the pathogenesis of GDM.

Early pregnancy loss (EPL) is a common event worldwide. Previous studies show that mitochondrial DNA (mtDNA) copy number (CN) is associated with semen parameters and preimplantation embryo viability, indicating the predictive potential of mtDNA CN for ongoing pregnancy outcomes. However, no relevant study has assessed the relationship between mtDNA CN and EPL. Thus, we aimed to determine whether mtDNA CN and mtDNA 4977-bp deletion rate (DR) in chorionic villous tissue are associated with EPL. Chorionic villous tissue total DNA was extracted from 75 EPL cases and 75 healthy controls. Chromosomal analysis was conducted using copy number variation (CNV) sequencing. The mtDNA CN and DR were measured in samples without pathogenic CNVs. The association between mtDNA CN or DR and EPL risk were estimated using logistic regression. The EPL group had a significantly different mtDNA CN (P 0.001) and DR (P = 0.005) compared to the control group. Both biomarkers were independent risk factors for EPL (CN odds ratio 1.71, 95% confidence interval 1.17 to 2.49, P = 0.005; DR odds ratio 1.07, 95% confidence interval 1.02 to 1.12, P = 0.006). These results suggest that higher mtDNA CN and DR levels are strongly associated with EPL and represent independent risk factors for EPL. Further studies validating these findings and exploring the underlying biological mechanisms are warranted.

Sucrose phosphorylase (SPase) is capable of specifically catalysing transglucosylation reactions and can be employed in the enzymatic synthesis of α-D-glycosides. In the present study, a putative Thermobacillus SPase gene (TSPase) was synthesised with optimised codons and overexpressed in Escherichia coli. The 1467 bp gene encodes a 488-amino acid protein with a calculated molecular mass of 55.8 kDa. The specific activity of the recombinant TSPase (rTSPase) was 6.42 U/mg for sucrose, and the optimum temperature and pH were 65 °C and pH 7.0. The T1/2 value of the rTSPase was 212 h at 50 °C and 98 h at 60 °C. A stimulating effect on the activity of the rTSPase was observed in the presence of 5 mM Co2+. The rTSPase showed increased stability against DMSO as organic co-solvent at 50 °C. The Km and kcat of the rTSPase with sucrose were determined as 6.24 mM and 5.73 s−1 respectively. The rTSPase produced 2-O-α-D-Glucopyranosyl-L-ascorbic acid (AA-2 G) from ascorbic acid in both crude extract and whole-cell forms. A maximum yield of 19.7% (39.94 ± 0.17 g/L) was achieved after incubation of ascorbic acid sodium salt and sucrose (1:2) with 19.76 U/mL of the rTSPase at pH 7.0 and 50 °C for 24 h.

A novel ratiometric fluorescence probe for hypochlorous acid was constructed by coumarin and pyridinium fluorophore based on the Forster resonance energy transfer (FRET) and intramolecular charge transfer (ICT) platform. In this ICT/FRET system, the energy transfer efficiency is high to 94.3%. Moreover, the probe could respond to hypochlorous acid with high selectivity and sensitivity, and exhibited a large Stokes shift. It was interesting to find that the probe could recognize hypochlorous acid via a new mechanism, in which the α-position of carbonyl group was oxidized to form a diketone derivative. More importantly, the probe was successfully applied to the ratiometric imaging of both exogenous and endogenous hypochlorous acid in living RAW 264.7 cells, with low toxicity and high photo-stability.

Current research on groundwater contamination due to mining tailing ponds seepage has concentrated on the toxicological effects of metals on organisms and ecosystems. However, recent studies found that the most hazardous pollutants that affect water quality in some rare earth metals smelting tailings pond are the large amount of ions but not metals. Whether these excess ions can cause genetic damage in organisms needs further study. Thus, the hazardous contaminant components in groundwater from five different sites in and near a rare earth elements (lanthanides) tailings pond were analyzed. Then, the biological damages to Sprague-Dawley (SD) rats caused by tailings seepage-contaminated groundwater at the individual, organ, tissue, and cellular levels were systematically studied. Following that, the correlations between the pollution components in the contaminated groundwater and tissue damages in SD rats were further analyzed. The results showed that the main hazardous pollution ions in the rare earth metals tailings seepage-contaminated water were F−, Cl−, and SO42−. Contamination was increasingly severe closer to the tailings dam. Water from the study sampling sites caused liver and kidney damage to the SD rats. Further, the results from microscopic morphology and flow cytometric apoptosis analyses showed that the damages caused to the kidney epithelia cells by F− and Cl− showed an increasing trend as the sites neared the tailings dam, and there were positive correlations. The effect of SO42− was not significant. Therefore, this study provides a foundation to scientifically and effectively evaluate the genetic damages caused to organisms by groundwater near tailings ponds, and also provides a theoretical basis to reveal the mechanism underlying this effect.

Background: Little is known about the population pharmacokinetics (PPK) of daptomycin in kidney transplant patients. The present study established a pharmacokinetic model for daptomycin in kidney transplant patients in China and examinee the important factors affecting the pharmacokinetic parameters of daptomycin. Methods: The study population included 49 kidney transplant patients with 537 daptomycin concentrations. The PPK model of daptomycin was developed using a nonlinear mixed-effects model, a two-compartment structural model, and a mixed residual error model. The stability and predictive ability of the final model were evaluated based on bootstrapping, visual prediction checks and normalized prediction distribution errors. Results: Glomerular filtration rate (GFR) and total body weight significantly affected clearance, and body weight influenced the central volume of distribution. The average clearance of the population was 0.316 L/h, the central volume of distribution was 6.04 L, the intercompartmental clearance was 2.31 L/h, and the peripheral volume of distribution was 2.46 L. Based on the established model and the target of area under curve (AUC0-24h)/minimum inhibition concentration (MIC) ≥666, we developed a recommended dose regimen for kidney transplant patients according to their renal function and weight. The daily doses were 4.0±0.31, 4.7±0.36, 5.1±0.40, 5.5±0.43, 5.8±0.45, and 6.1±0.48 mg/kg when the GFRs were 15, 30, 45, 60, 75, and 90 ml/min/1.73 m2, respectively. Conclusion: This study provides a reference for individualized daptomycin administration in kidney transplant recipients, and it is a valuable resource for improving the treatment effect and reducing the toxic effects of daptomycin.

We explored whether red blood cell distribution width (RDW), a routinely checked item of complete blood cell counts, was an indicator of long-term euglycemia remission in patients with type 2 diabetes after short-term continuous subcutaneous insulin infusion (CSII).We analyzed the original data of patients enrolled in three randomized control trials from 2002 to 2014. CSII was administered to drug-naїve patients with newly diagnosed type 2 diabetes to achieve and maintain euglycemia for 2weeks.A total of 185 patients were involved and 98 patients (52.97%) who achieved and maintained euglycemia for at least 12months were classified as the remission group, and the others as the non-remission group. Patients in remission group had a relatively lower value for baseline RDW (38.82±2.76vs 39.89±2.78fL, p=0.017) compared with those in non-remission group. A graded decrease of remission rate (67.50%, 55.00%, 53.66% and 30.77% for Quartile 1 to Quartile 4 respectively, P0.05) was observed with the increasing of RDWs. The risk of hyperglycemic relapse was significantly increased for those in the highest quartile compared with the lowest (hazard ratio=2.68; 95% CI, 1.38-5.22). Those who achieved euglycemia within 7days or obtained a better fasting glucose after therapy had preferable remission rates.Patients with lower baseline RDWs are more likely to maintain a one-year euglycemia remission after short-term CSII. A faster normalization of glucose during treatment and a lower fasting glucose after therapy are correlated with a long-term glucose control.

Micro-structured components have been widely used in modern opto-electronics systems, but effective characterization methods for structured surfaces are still of lack. Reliable filtering is required to separate the salient structural features and micro-textures, so that the characteristic parameters of the geometrical features can be obtained accurately. Conventional filtering methods cannot preserve sharp features very well. In this paper, a feature-preserving filtering method is proposed using the combined sparse regularizers. In addition to the fidelity term, two regularization terms involving the first order and second order derivatives respectively are taken in the optimization objective function, so that the filtered data can be divided into a piecewise constant part and a piecewise smooth part. Taking the advantage of sparsity of l p -norm (0

ObjectiveTo discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate.Materials and MethodsWe propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014.ResultsWe apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (~0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC).DiscussionExpert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our framework leverages machine learning and feature engineering to loosen such selection criteria to achieve a high identification rate of cases and controls.ConclusionsOur proposed framework demonstrates a more accurate and efficient approach for identifying subjects with and without T2DM from EHR.

In this study, the welding-brazing process of pulsed double electrode gas metal arc welding (pulsed DE-GMAW) provides a potential method to join dissimilar metals (i.e., joining of aluminum alloys to galvanized mild steel). In order to evaluate the stability of welding process, a mathematical model of the alternation of droplet transfer for the pulsed DE-GMAW is established based on the spring-mass-damper model. The droplet alternative transfer is a free flight with short circuiting transfer mode, which is analyzed and detected during the welding process with double pulsed current. Meanwhile, the pulsed DE-GMAW technology is found to be feasible to join the aluminum alloys to the galvanized mild steel. The variable weldability process of aluminum-galvanized steel could be obtained with a wire by optimizing welding parameters. Microstructures of the intermetallic reaction layer and bonding mechanism of optimized weld-brazed specimens with aluminum ER4043 and ER5356 wires are analyzed and conducted by SEM and tensile test.

Two-dimensional (2D) nano-structured tin monoxide (SnO) offers fascinating possibilities as anode material for lithium ion batteries (LIBs). 2D architectures of SnO are highly desirable to access advanced lithium storage properties however their application is impeded by the lack of synthetic method. In this study, we report a scalable synthetic route to facilely deriving SnO/pristine-graphene (p-G) 2D-2D heterostructure from bulk SnO and graphite. A “top-down” synthetic method was found effective in transforming SnO micro-sized particles into nanosheets down to a few nanometers in thickness. Assembled with pristine graphene (p-G), the SnO nanosheets were used to build a SnO/p-G heterostructure that delivers remarkable Li-ion storage performances: reversible capacities of 633.9 mAh g−1 after 100 cycles at 0.05 A g−1, and excellent cycling stabilities (0.027% capacity fade per cycle at 1 A g−1 after 700 cycles) were obtained. In comparison, raw SnO exhibited severe SEI over-growth and continuous capacity decay from the on-set at 0.05 A g−1. The structural advantages of 2D-2D heterostructure were elucidated to understand its exceptional lithium storage properties. This study demonstrates a facile and scalable strategy for producing 2D-2D heterostructures from low-cost bulk materials for LIBs application.

With the development of precision engineering, higher manufacturing qualities are demanded for advanced optical components. Subsequently characterization of surface topographies is demanded to be more specific and more comprehensive. The methods defined in ISO standards concerns only the overall statistical properties of surfaces, thus they are not applicable to non-stochastic surfaces. The second generation curvelet transform, which provides a sparse representation and good multiscale decomposition performance for curve singularities, is utilized as a powerful tool for the characterization of surface topographies. An effective method is also developed to identify and extract the topography features of interest in the domain of curvelets. Numerical experiments are given to show the effectiveness of this algorithm in sparse representation and feature separation of structured surfaces containing surface waviness, defects, tool marks and irregular scratches.

Nowadays freeform components are more and more commonly employed in precision engineering and it is crucial to evaluate their form qualities. The widely adopted PV parameters for form errors need to be evaluated in the sense of minimum zone, which is a non-differentiable optimization problem, and very difficult to be solved. Currently NURBS has become a ubiquitous data format in computer aided design and manufacturing. However, little can be found concerning the minimum zone fitting between the NURBS surfaces and measured data, due to the mathematical complexity of this problem. A fast evaluation strategy is proposed in this paper. It is implemented in three stages. The NURBS model is decomposed into Bezier patches first and the iterative closest point matching is implemented. And then the relative position is refined by the orthogonal distance least squares fitting. Finally the minimum zone fitting is carried out by the primal-dual interior point method. The solutions are recursively updated by line search until the Karush-Kuhn-Tucker conditions are satisfied. Numerical experiments proved that the proposed method is capable of minimum zone fitting for freeform NURBS surfaces with very high accuracy and efficiency.

High precision 3D profile rotary measuring systems for large diameter workpieces are urgently needed in precision engineering. Error separation is critical for improving the accuracy of the system. In order to obtain higher accuracy for 3D profile rotary measuring systems, the random and systematic errors are analyzed and separated in this paper. In the measuring system, roll and pitch caused by the probe tilt violate the Abbe principle. Roll is removed by using two probes and pitch is separated by the interferometer method. The radial run-out and the perpendicularity error between the probe and the spindle axis are compensated by a two-probe-two-step method carried out on a standard hemisphere artifact. As the form error of the artifact is mixed with the perpendicularity error, the least-squares method is applied to fit the hemisphere and work out the perpendicularity error and the profile error of the hemisphere. Finally, numerical validation is presented using Matlab program to demonstrate the effectiveness and correctness of the proposed method.

The low diffusion (LD) particle method, proposed by Burt and Boyd, is modified for the near-continuum two-phase flow simulations. The LD method has the advantages of easily coupling with the direct simulation Monte Carlo (DSMC) method for multi-scale flow simulations and dramatically reducing the numerical diffusion error and statistical scatter of the equilibrium particle methods. Liquid- or solid-phase particles are introduced in the LD method. Their velocity and temperature updating are respectively, calculated from the motion equation and the temperature equation according to the local gas properties. Coupling effects from condensed phase to gas phase are modeled as momentum and energy sources, which are respectively, equal to the negative values of the total momentum and energy increase in liquid or solid phase. The modified method is compared with theoretical results for unsteady flows, and good agreements are obtained to indicate the reliability of the one-way gas-to-particle coupling models. Hybrid LD–DSMC algorithm is implemented and performed for nozzle discharging gas–liquid flow to show the prospect of the LD–DSMC scheme for multi-scale two-phase flow simulations.

Star-block quadripolymers PEI-g-(PLF-b-PLL-b-PEG) and PEI-g-(PLF-b-PLG-b-PEG) [i.e., a polyethylenimine (PEI) core, an amphiphilic copolypeptide poly(l-phenylalanine)-b-poly(l-lysine) (PLF-b-PLL) or poly(l-phenylalanine)-b-poly(l-glutamic acid) (PLF-b-PLG) inner shell, and a poly(ethylene glycol) (PEG) outer shell] were synthesized, characterized, and evaluated as drug nanocarriers. The star-block quadripolymers were obtained by sequential ring-opening polymerizations of l-phenylalanine N-carboxyanhydride and e-benzyloxycarbonyl-l-lysine N-carboxyanhydride or γ-benzyl-l-glutamate N-carboxyanhydride initiated by the terminal primary amines of PEI. Subsequently, the periphery was PEGylated, and the poly(l-lysine) or poly(l-glutamic acid) side chains were deprotected. The synthesized star-block quadripolymers were characterized with 1H NMR, gel permeation chromatography (GPC), and laser light dynamic scattering (DLS). These polymers were well dispersed in aqueous solutions and resembled amphiphilic unimolecular micelles. The encapsulation study demonstrated that these polymers can solubilize nonpolar model compounds through hydrophobic interactions. Dialysis and spectrophotometric titration experiments indicated that these polymers could efficiently encapsulate hydrophilic model compounds via electrostatic interactions. Furthermore, the synthesized quadripolymers could entrap hydrophobic and hydrophilic model compounds in the site-isolated state simultaneously. The entrapped hydrophilic model compounds demonstrated sustained release at physiological pH and accelerated release when the pH was either increased or decreased. The simultaneous encapsulation of versatile guest molecules as well as the pH-responsive releasing properties of these star-block quadripolymers could be potentially useful in the controlled drug co-delivery applications.

A hydrophilic star block co-polymer was synthesized, characterized, and evaluated as a protein nanocarrier. The star block co-polymer was composed of a hyperbranched polyethylenimine (PEI) core, a poly( l -lysine) (PLL) inner shell, and a poly(ethylene glycol) (PEG) outer shell. The model protein insulin can be rapidly and efficiently encapsulated by the synthesized polymer in aqueous phosphate buffer at physiological pH. Complexation between PEI–PLL–b-PEG and insulin was investigated using native polyacrylamide gel electrophoresis. The uptake of enhanced green fluorescent protein into Ad293 cells mediated by PEI–PLL–b-PEG was also investigated. The encapsulated insulin demonstrated sustained release at physiological pH and showed accelerated release when the pH was decreased. The insulin released from the star block co-polymer retained its chemical integrity and immunogenicity.

Cylindrical copolypeptide brushes PLLF-g-(PLF-b-PLG) with poly( l -lysine-co- l -phenylalanine) (PLLF) as the backbone and poly( l -phenylalanine)-b-poly( l -glutamic acid) (PLF-b-PLG) as the side chains have been synthesized and evaluated as drug delivery carriers. The synthesized copolypeptide brushes were characterized by 1H NMR, gel permeation chromatography (GPC), and transmission electron microscopy (TEM). In aqueous solution, the copolypeptide brushes adopt cylindrical morphologies and resemble unimolecular polymeric micelles with a hydrophobic poly( l -phenylalanine) core and a hydrophilic poly( l -glutamate) shell. An encapsulation study demonstrated that these water soluble, biodegradable copolypeptide brushes encapsulate hydrophobic compounds and cationic hydrophilic guest molecules simultaneously. Furthermore, the encapsulated cationic model compounds exhibit a pH-responsive releasing property.

Star-block copolymers PEI- g -(PLL- b -PEG) with a branched polyethylenimine (PEI) core, a poly( l -lysine) (PLL) inner shell, and a poly(ethylene glycol) (PEG) outer shell have been synthesised and evaluated as potential nanocarriers for anionic drugs. The star-block copolymers were synthesised by a ring-opening polymerisation of ɛ-benzyloxycarbonyl- l -lysine N -carboxyanhydride initiated by the peripheral primary amino groups of PEI, surface modification with activated PEG 4-nitrophenyl carbonate, and subsequent deprotection of benzyl groups on the side chains of the PLL inner shell. The synthesised star-block copolymers were characterised by 1 H NMR, gel permeation chromatography (GPC), and dynamic light scattering (DLS). The encapsulation properties of these star-block copolymers were characterised by spectrophotometric titration and dialysis. These techniques demonstrated that anionic model dyes, such as methyl orange and rose Bengal, and the model drug diclofenac sodium can be encapsulated efficiently by PEI- g -(PLL- b -PEG) at physiological pH. The entrapped model compounds demonstrated sustained release at physiological pH and accelerated release when the pH was either increased to 10.0–11.0 or decreased to 2.0–3.0. The efficient encapsulation as well as the pH-responsive releasing properties of these star-block copolymers could be potentially used in the controlled release of anionic drugs.

When lunar modules land on the Moon, dust impingement on the lunar module components and deposition on the thermal and optical surfaces would cause many serious problems. The emphasis of this research is on simulating the interaction of rocket plume and lunar dust using the direct simulation Monte Carlo (DSMC) method. The method is extended to model the movement and collision stages of rarefied plume gas and dust particles, including three collisional mechanisms: molecule–molecule, molecule–particle and particle–particle collisions. The reflection of gas molecules on the particle surface is computed by an indirect approach based on the coordinate transformation. Neighboring-cell contact detection scheme is applied to check for contacts between all possible particle pairs. The simulation results show that the acceleration of dust particle is mostly determined by the parameters of plume field. In the computational regions with larger gas density and velocity the particles can be accelerated to larger velocity and convected to higher temperature.

Four surfactant-type peroxotungstates and peroxomolybdates have been synthesized and characterized. Their catalytic activities for 30 wt.% H2O2 oxidation of cyclohexene, cyclohexanol, cyclohexanone and 1,2-cyclohexanediol to adipic acid were evaluated without organic solvent and phase-transfer catalyst. The surfactant-type polyoxoperoxometalates act as not only a catalyst but also a phase-transfer agent, which can form the emulsion droplets. The emulsion droplets are in the highly dispersed form and behave like homogeneous catalysts with high activities. Long carbolic chain cation assembled in the interface of the emulsion droplets, peroxotungsten anion-containing catalysts exhibited high activities. However, peroxomolybdenum anion-containing catalysts exhibited low activities.

An analytical method is proposed for calculating reflection-spectrum envelope of interleaved sampled gratings with phase-shifts. Effects of parameters on reflection-spectrum envelope of the grating are discussed, such as two grating segment lengths, phase-shift and interleaved length. The unique optimal interleaved length can be obtained to provide the broadest flat-top reflection-spectrum envelope without ripples. Accuracy of the analytical expression is verified due to the calculated results in good agreement with the reflection spectra obtained by the piecewise uniform transform matrix method.

Combination of equivalent reflection cavity model and transmission line theory is applied in theoretical analysis of external cavity semiconductor lasers with sampled fiber Bragg grating. The effects of device parameters on the resonant cavity mode and the side mode suppression ratio have been discussed. For a perfect anti-coated facet and the high coupling efficiency, it is found that the Vernier effect between combed reflectivity peaks and F–P cavity modes can be destroyed and the laser will work on multi-wavelength. The high coupling efficiency plays the same role as the lower anti-reflection coating reflectivity in the side mode suppression ratio and the mode resonance. Finally, the side mode suppression ratio is investigated in detail depending on the anti-coating reflectivity, the coupling efficiency and the high-reflection coating reflectivity.

Background. Women with ovarian cancer who experience disease progression during or within 6 months of first-line treatment with platinum-based anticancer drugs are considered to have platinum-resistant tumors. These patients have an unfavorable prognosis, and they frequently seek complementary and alternative therapies (CAM). Historically, this represents an understudied and underreported component of ovarian cancer treatment. Case. This report describes the case of a woman with rapidly progressive, platinum-resistant ovarian cancer. Upon initiating self-directed treatment with Haelan951®, a commercially available fermented soy beverage, she entered into a phase of prolonged disease stabilization including improvement in the serum tumor marker CA-125. Conclusion. Fermented soy products are known to contain high concentrations of the isoflavone, genistein, and other compounds that exhibit anticancer activity in preclinical models. This case report supports the prospective evaluation of alternative therapies such as these in patients with platinum-refractory ovarian cancer.

Radiolabeled tyrosine is incorporated into newly biosynthesized tunichrome of Ascidia ceratodes at a rate comparable to previous findings with phenylalanine. 3H-tyrosine incorporation indicates that formation of the catechol and pyrogallol moieties occurs via the NIH shift pathway. Radiolabel is found in many compartments other than solely tunichrome (tunic > whole body ⪢ blood plasma ⋙ tunichrome). The amount of label in the tunic, whole bodies and blood plasma declines over the 14 days following exposure to 3H-tyrosine, whereas the radiolabel in the tunichrome continues to increase. These results are consistent with two alternative hypotheses: tunichromes may be formed either by sequential hydroxylation of di- and tri-peptide precursors, or by selective cleavage of a larger DOPA- or TOPA-containing compound. In either event, hydroxylation may precede formation of tunichrome's carbon backbone.

We describe a novel pyruvate selective sensor in which corn tissue, as the biocatalytic layer, is coupled to a fluorescent indicator-based fiber-optic CO2 optrode. This sensor showed shorter response times and a lower detection limit without loss of enzymatic stability as compared to a corn tissue-based pyruvate selective membrane electrode previously studied.