Measurement of Cerebral Glucose Utilization Using Washout After Carotid Injection in the Rat

Abstract: The carotid injection technique, used previously to quantitate the kinetics of blood-brain barrier transport of metabolic substrates, may be modified to analyze the rate of cerebral glucose utilization. A 0.2-ml solution of [¹⁴C]glucose (G_F) and [³H]methylglucose (M), an internal reference, is rapidly injected into the carotid artery, followed by microwave fixation of brain at various times up to 4 min after injection. The brain radioactivity is separated into a fraction containing neutral hexoses (G_F and M) and a fraction containing metabolites of glucose. The G_F/M ratio is related to the rate constant (k₃) of brain glucose utilization by the simple, linear equation: In(G_F/M) = In(G_F°/M°) –k₃t, where G_F°/M°= the brain uptake index of glucose, relative to methylglucose, at 5-15 s after injection, and t= the time after carotid injection, e.g., 1–4 min. It is assumed that (a) the rate of influx due to recirculation of label is minimal during the 4-min circulation period; and (b) the rate constants of glucose efflux (k₂) and methylglucose efflux (k₂*) are identical. Independent estimates of k₂ and k₂* showed these parameters to be identical: k₂= 0.14 + 0.08 min-I; k₂*= 0.14 ± 0.02 min-I. A logarithmic plot of G_F/M ratios versus time was linear (r = 0.99), and was described by the slope k₂= 0.21 ± 0.02 min^?1. Assuming glucose is uniformly distributed in brain, then the glycolytic rate = k₃× brain glucose = (0.21 min^?1) (2.6 μmol g^?1) = 0.55 μmol min^?1 g^?1 for the cortex of the barbiturate-anesthetized rat. These studies provide the basis for a simple method of measurement of regional brain glycolysis that does not require either the use of correction factors, e.g., the lumped constant, or the use of differentially labeled glucose.     

Batch kinetic studies of glucose isomerization to fructose by Arthrobacter species

Glucose can be isomerized to fructose by the catalytic action of the enzyme, glucose isomerase. This enzyme is synthesized by a variety of micro-organisms, predominantly by bacteria. Arthrobacter species cells are grown in a medium standardized specifically to synthesize the enzyme and are then used to isomerize glucose under conditions of no further cell growth. Effect of metal ions on the isomerization is studied and it is found that magnesium promoted the reaction, sodium had no effect and calcium and manganese inhibited the reaction. Rate of reaction per unit of catalyst is found to be constant. Michaelis-Menten model modified for the reversibility of the reaction is suitable to describe the isomerization kinetics and the kinetic parameters are determined and reported.List of Symbols k ₁ rate constant (Glucose to intermediate complex) - k _–1 rate constant (Intermediate complex to glucose) - k ₂ rate constant (Intermediate complex to fructose) - k _–2 rate constant (Fructose to intermediate complex) - v _mf maximum reaction velocity of the forward (GF) reaction - v _mb maximum reaction velocity of the reverse (FG) reaction - K _f Michaelis-Menten constant for the forward (GF) reaction - K _b Michaelis-Menten constant for the reverse (FG) reaction - K _eq equilibrium constant - r _G rate of glucose consumption     

Observer design for differential-algebraic model of an aerobic culture of a recombinant yeast

The mathematical model of an aerobic culture of recombinant yeast presented in work by Zhang et al. (1997) is given by a differential-algebraic system. The classical nonlinear observer algorithms are generally based on ordinary differential equations. In this paper, first we extend the nonlinear observer synthesis to differential-algebraic dynamical systems. Next, we apply this observer theory to the mathematical model proposed in Zhang et al. (1997). More precisely, based on the total cell concentration and the recombinant protein concentration, the observer gives the online estimation of the glucose, the ethanol, the plasmid-bearing cell concentration and a parameter that represents the probability of plasmid loss of plasmid-bearing cells. Numerical simulations are given to show the good performances of the designed observer.Symbols C ₁ activity of pacing enzyme pool for glucose fermentation (dimensionless) - C ₂ activity of pacing enzyme pool for glucose oxidation (dimensionless) - C ₃ activity of pacing enzyme pool for ethanol oxidation (dimensionless) - E ethanol concentration (g/l) - G glucose concentration (g/l) - k _a regulation constant for (g glucose/g cell h^–1) - k _b regulation constant for (dimensionless) - k _c regulation constant for (g glucose/g cell h^–1) - k _d regulation constant for (dimensionless) - K _m1 saturation constant for glucose fermentation (g/l) - K _m2 saturation constant for glucose oxidation (g/l) - K _m3 saturation constant for ethanol oxidation (g/l) - L ( t) time lag function (dimensionless) - p probability of plasmid loss of plasmid-bearing cells (dimensionless) - P recombinant protein concentration (mg/g cell) - q _G total glucose flux culture time (g glucose/g cell h) - t culture time (h) - t _lag lag time (h) - X total cell concentration (g/l) - X ⁺ plasmid-bearing cell concentration (g/l) - Y ^F _{X / G} cell yield for glucose fermentation pathway (g cell/g glucose) - Y ^O _{X / G} cell yield for glucose oxidation pathway (g cell/g glucose) - Y _{X / E} cell yield for ethanol oxidation pathway (g cell/g ethanol) - Y _{E / X} ethanol yield for fermentation pathway based on cell mass (g ethanol·g cell) - ₂ glucoamylase yield for glucose oxidation (units/g cell) - ₃ glucoamylase yield for ethanol oxidation (units/g cell) - µ₁ specific growth rate for glucose fermentation (h^–1) - µ₂ specific growth rate for glucose oxidation (h^–1) - µ₃ specific growth rate for ethanol oxidation (h^–1) - µ_1max maximum specific growth rate for glucose fermentation (h^–1) - µ_2max maximum specific growth rate for glucose oxidation (h^–1) - µ_3max maximum specific growth rate for ethanol oxidation (h^–1)     

Characterization of centromere arrangements and test for random distribution in G0, G1, S,G2, G1, and early S′ phase in human lymphocytes

Summary The arrangement of centromeres, cluster formation and association with the nucleolus and the nuclear membrane were characterized in human lymphocytes during the course of interphase in a cell-phase-dependent manner. We evaluated 3 893 cell nuclei categorized by five parameters. The centromeres were visualized by means of indirect immunofluorescent labeling with anti-centromere antibodies (ACA) contained in serum of patients with CREST syndrome. The cell nuclei were classified as G₀, G₁, S, G₂, Gl₁ and early S phase by comparing microscopically identified groups of cell nuclei with flow cytometric determination of cell cycle stage of synchronized and unsynchronized lymphocyte cell cultures. Based on a discrimination analysis, a program was devised that calculated the probability for any cell nucleus belonging to the G₀, G₁, S, G₂, G₁ and early S phase using only two microscopic parameters. Various characteristics were determined in the G₀, S, and G₂ stages. A transition stage to S phase within G₁ was detected. This stage shows centromere arrangements not repeated in later cell cycles and which develop from the dissolution of centromere clusters in the periphery of the nucleus during G₀ and G₁. S phase exhibits various non-random centromere arrangements and associations of centromeres with the nucleolus. G₁ and early S phase of the second cell cycle display no characteristic centromere arrangement. The duplication of centromeres in G₂ is asynchronous in two phases. For all cell phases a test for random distribution of the centromeres in the cell nucleus was performed. There is a distinct tendency for centromeres to be in a peripheral position during Go and G₁; this tendency becomes weaker in S phase. Although the visual impression is a seemingly random distribution of centromeres in G₂ and G₁ statistical analysis still demonstrates a significant deviation from random distribution in favor of a peripheral location. Only the early S phase of the second cell cycle shows no significant deviation from a random distribution.     

Performance,kinetics, and substrate utilization in a continuous yeast fermentation with cell recycle by ultrafiltration membranes

Summary A continuous single stage yeast fermentation with cell recycle by ultrafiltration membranes was operated at various recycle ratios. Cell concentration was increased 10.6 times, and ethanol concentration and fermentor productivity both 5.3 times with 97% recycle as compared to no recycle. Both specific growth rate and specific ethanol productivity followed the exponential ethanol inhibition form (specific productivity was constant up to 37.5 g/l of ethanol before decreasing), similar to that obtained without recycle, but with greater inhibition constants most likely due to toxins retained in the system at hight recycle ratios.By analyzing steady state data, the fractions of substrate used for cell growth, ethanol formation, and what which were wasted were accounted for. Yeast metabolism varied from mostly aerobic at low recycle ratios to mostly anaerobic at high recycle ratios at a constant dissolved oxygen concentration of 0.8 mg/kg. By increasing the cell recycle ratio, wasted substrate was reduced. When applied to ethanol fermentation, the familiar terminology of substrate used for Maintenance must be used with caution: it is not the same as the wasted substrate reported here.A general method for determining the best recycle ratio is presented; a balance among fermentor productivity, specific productivity, and wasted substrate needs to be made in recycle systems to approach an optimal design.Nomenclature B Bleed flow rate, l/h - C _T Concentration of toxins, arbitrary units - D Dilution rate, h^-1 - F Filtrate or permeate flow rate, removed from system, l/h - F _o Total feed flow rate to system, l/h - K _s Monod form constant, g/l - P Product (ethanol) concentration, g/l - P _o Ethanol concentration in feed, g/l - PP} Adjusted product concentration, g/l - PD Fermentor productivity, g/l-h - R Recycle ratio, F/F _o - S Substrate concentration in fermentor, g/l - S _o Substrate concentration in feed, g/l - V Working volume of fermentor, l - V _MB Viability based on methylene blue test - X Cell concentration, g dry cell/l - X _o Cell concentration in feed, g/l - Y _ATP Cellular yield from ATP, g cells/mol ATP - Y _ATPS Yield of ATP from substrate, mole ATP/mole glucose - Y _G True growth yield or maximum yield of cells from substrate, g cell/g glucose - Y _P Maximum theoretical yield of ethanol from glucose, 0.511 g ethanol/g glucose - Y _P/S Experimental yield of product from substrate, g ethanol/g glucose - Y _x/s Experimental yield of cells from substrate, g cell/g glucose - S _NP/X Non-product associated substrate utilization, g glucose/g cell - k ₁, k₂, k₃, k₄ Constants - k ₁ ^APP , k ₂ ^APP Apparent k ₁, k₃ - k ₁ ^TRUE True k ₁ - m Maintenance coefficient, g glucose/g cell-h - m ^* Coefficient of substrate not used for growth nor for ethanol formation, g glucose/g cell-h - Specific growth rate, g cells/g cells-h, reported as h^-1 - _m Maximum specific growth rate, h^-1 - v Specific productivity, g ethanol/g cell-h, reported as h^-1 - v _m Maximum specific productivity, h^-1     

Radiosensitivity and recovery of mouse L cells during the cell cycle

Summary Mouse fibroblasts, subline L-929 F were synchronized by mitotic detachment. The synchronized cell cultures were irradiated with 200 kVp X-rays at different time after mitosis, and age reponse functions and dose effect curves were determined using the colony test. The cell age in the mitotic cycle was obtained from a computer analysis of flow cytometric DNA histograms. Both intrinsic radiosensitivity 1/D ₀ and extrapolation numbern were found to vary during the cell cycle. TheD ₀ has a maximum value of 176 ± 1 rad in the middle ofG ₁ phase and a minimum of 71 ± 1 rad at theS/G ₂ transition, while the extrapolation number is rather constant from the beginning ofG ₁ phase (1.9 ± 0.1) to the middle ofS phase (2.3 ± 0.1) and reaches a steep maximum of 9.3 ± 1.1 atS/G ₂ transition. The values ofn in the various phases of cell cycle are compared with the respective values of the recovery factor determined after fractionated irradiation. - Cell survival after a single dose of 616 rad has minima for irradiation atG ₁/S transition and in earlyG ₂ phase; the survival in earlyG ₂ being about 40 times smaller than in earlyG ₁ phase. Implications for a cell cycle specific therapy are discussed.Supported by the Deutsche Forschungsgemeinschaft, Bonn-Bad Godesberg     

Start-up sensitivity to the initial state of a batch bioreactor for a recombinant Escherichia coli in a complex medium

The sensitivities with respect to the initial state of five key variables describing the performance of a batch bioreactor have been computed from an experimentally validated kinetic model. The system has a recombinant Escherichia coli strain containing the plasmid pBR Eco gap, which codes for glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in a complex medium. Since previous studies have shown the start-up sensitivities to be particularly important, the initial 10% of the duration of fermentation was chosen as the time span. The sensitivities of the cell mass, GAPDH and acetate increased with time while those of glucose and yeast extract remained practically constant.Acetate has a crucial role as it functions as both a product and a reactant. With no acetate in the inoculum, the sensitivities of acetate increased an order of magnitude faster than other sensitivities. However, upon addition of acetate through the inoculum, its sensitivities decreased the fastest and stabilised beyond a starting concentration of about 1 g/l whereas other sensitivities stabilised after 5 to 6 g/l of initial acetate. A three-dimensional envelope in the space of acetate concentration-time-relative sensitivity shows a locus of concentrations for minimum time-dependent acetate sensitivity; this may be maintained through fed-batch operation.List of Symbols a A/A₀ - A g/l initial concentration at any time - A ₀ g/l initial acetate concentration - e E/E₀ - E g/l yeast extract concentration at any time - E ₀ g/l initial yeast extract concentration - g G/G₀ - G g/l glucose concentration at any time - G ₀ g/l initial glucose concentration - k _A ^A g/l inhibition constant for acetate-dependent growth during the acetate phase - k _A ^G g/l inhibition constant for acetate-dependent growth during the glucose phase - k _M ^A 1/h rate constant for acetate phase - k _M ^G 1/h rate constant for glucose phase - K _A g/1 affinity constant for acetate - K _G g/1 affinity constant for glucose - m ^A 1/h coefficient of maintenance in acetate - m _m ^A 1/h maximum value of m ^A - m ^G 1/h coefficient of maintenance in glucose - m _m ^G 1/h maximum value of m ^G - n empirical constant - P P/P₀ - P U/ml GAPDH concentration at any time - P ₀ U/ml initial GAPDH concentration - s _c (i,j) sensitivity of y _i to y _j(0) for A ₀=c - t h time - x X/X₀ - X g/l cell mass concentration at any time - X ₀ g/l initial cell mass concentration - y ₁ x - y₂ g - y₃ a - y₄ e - y ₅ p - y _x/A ^A g/g yield coefficient for cell mass per unit mass of acetate during acetate phase - y _x/A ^G g/g yield coefficient for cell mass per unit mass of acetate during glucose phase - y _x/G g/g yield coefficient for cell mass per unit mass of glucose - y _E/x ^A g/g yield coefficient for yeast extract per unit cell mass during acetate phase - y _P/x ^A g/g yield coefficient for yeast extract per unit cell mass during glucose phase - y _P/x ^A U/g yield coefficient for GAPDH per unit cell mass during acetate phase - y _P/x ^G U/g yield coefficient for GAPDH per unit cell mass during glucose phase Greek Letters ₀ proportionality constant for plasmid loss probability - ₁ 1/h maximum rate of plasmid replication - ₂ 1/h saturation constant of the host component of plasmid replication - regulation function (0 or 1) - regulation function (0 or 1) - exponent of growth inhibition term for acetate during the acetate phase - exponent of growth inhibition term for acetate during the glucose phase - ^A 1/h specific growth rate during acetate phase - _m ^A 1/h maximum value of ^A - ^G 1/h specific growth rate during glucose phase - _m ^G 1/h maximum value of ^G - _c (i,j) ratio of sensitivities, s _c (i,j)/s ₀(i,j) - nondimensional time, t _m ^G      

Cell Cycle Dynamics of Cultured Coral Endosymbiotic Microalgae (Symbiodinium) Across Different Types (Species) Under Alternate Light and Temperature Conditions

Dinoflagellates of the genus Symbiodinium live in symbiosis with many invertebrates, including reef‐building corals. Hosts maintain this symbiosis through continuous regulation of Symbiodinium cell density via expulsion and degradation (postmitotic) and/or constraining cell growth and division through manipulation of the symbiont cell cycle (premitotic). Importance of premitotic regulation is unknown since little data exists on cell cycles for the immense genetic diversity of Symbiodinium. We therefore examined cell cycle progression for several distinct SymbiodiniumITS2‐types (B1, C1, D1a). All types exhibited typical microalgal cell cycle progression, G₁ phase through to S phase during the light period, and S phase to G₂/M phase during the dark period. However, the proportion of cells in these phases differed between strains and reflected differences in growth rates. Undivided larger cells with 3n DNA content were observed especially in type D1a, which exhibited a distinct cell cycle pattern. We further compared cell cycle patterns under different growth light intensities and thermal regimes. Whilst light intensity did not affect cell cycle patterns, heat stress inhibited cell cycle progression and arrested all strains in G₁ phase. We discuss the importance of understanding Symbiodinium functional diversity and how our findings apply to clarify stability of host‐Symbiodinium symbioses.     

ARTD1 regulates cyclin E expression and consequently cell-cycle re-entry and G1/S progression in T24 bladder carcinoma cells

ADP-ribosylation is involved in a variety of biological processes, many of which are chromatin-dependent and linked to important functions during the cell cycle. However, any study on ADP-ribosylation and the cell cycle faces the problem that synchronization with chemical agents or by serum starvation and subsequent growth factor addition already activates ADP-ribosylation by itself. Here, we investigated the functional contribution of ARTD1 in cell cycle re-entry and G₁/S cell cycle progression using T24 urinary bladder carcinoma cells, which synchronously re-enter the cell cycle after splitting without any additional stimuli. In synchronized cells, ARTD1 knockdown, but not inhibition of its enzymatic activity, caused specific down-regulation of cyclin E during cell cycle re-entry and G₁/S progression through alterations of the chromatin composition and histone acetylation, but not of other E2F-1 target genes. Although Cdk2 formed a functional complex with the residual cyclin E, p27^{Kip1 Murray AH, Hunt T. The cell cycle: an introduction. New York: Oxford University Press, 1993. [Google Scholar]} protein levels increased in G₁ upon ARTD1 knockdown most likely due to inappropriate cyclin E-Cdk2-induced phosphorylation-dependent degradation, leading to decelerated G₁/S progression. These results provide evidence that ARTD1 regulates cell cycle re-entry and G₁/S progression via cyclin E expression and p27^{Kip1 Murray AH, Hunt T. The cell cycle: an introduction. New York: Oxford University Press, 1993. [Google Scholar]} stability independently of its enzymatic activity, uncovering a novel cell cycle regulatory mechanism.     

A kinetic model and simulation of starch saccharification and simultaneous ethanol fermentation by amyloglucosidase and Zymomonas mobilis

A mathematical model is described for the simultaneous saccharification and ethanol fermentation (SSF) of sago starch using amyloglucosidase (AMG) and Zymomonas mobilis. By introducing the degree of polymerization (DP) of oligosaccharides produced from sago starch treated with -amylase, a series of Michaelis-Menten equations were obtained. After determining kinetic parameters from the results of simple experiments carried out at various substrate and enzyme concentrations and from the subsite mapping theory, this model was adapted to simulate the SSF process. The results of simulation for SSF are in good agreement with experimental results.List of Symbols g/g rate coefficient of production - _max 1/h maximum specific growth rate - E %, v/w AMG concentration - G ₁ mmol/l glucose concentration - G _c mmol/l glucose concentration consumed - G _f mmol/l glucose concentration formed - G _n mmol/l n-mer maltooligosaccharide concentration - K _i g/l ethanol inhibition constant for ethanol production - K _g mmol/l glucose inhibition constant for glucose production - K _p mmol/l glucose limitation constant for ethanol production - K _x mmol/l glucose limitation constant for cell growth - K _m,n mmol/l Michaelis-Menten constant for n-mer oligosaccharide - k _e %, v/w enzyme limitation constant - k _es proportional constant - k _{max, n} 1/s maximal velocity for n-mer digestion - k _s g/l substrate limitation constant - m _s g/g maintenance energy - MW _n g/mol molecular weight of n-mer oligosaccharide - P g/l ethanol concentration - P ₀ g/l initial ethanol concentration - P _m g/l maximal ethanol concentration - Q _pm g/(g · h) maximum specific ethanol production rate - S _n mmol/h branched n-mer oligosaccharide concentration - S ₀ g/l initial starch concentration - S _sta g/l starch concentration - S _tot g/l total sugar concentration - V _{max, n} 1/h maximum digestion rate of n-mer oligosaccharide - V ₀ g/(l · h) initial glucose formation rate - X g/l cell mass - X ₀ g/l initial cell mass - Y _p/s g/g ethanol yield - Y _x/s g/g cell mass yield     

Cell cycle kinetics of the accumulation of heavy and light chain immunoglobulin proteins in a mouse hybridoma cell line

Rates of accumulation of immunoglobulin proteins have been determined using flow cytometry and population balance equations for exponentially growing murine hybridoma cells in the individual G₁, S and G₂+M cell cycle phases. A producer cell line that secretes monoclonal antibodies, and a nonproducer clone that synthesizes only -light chains were analyzed. The pattern for the kinetics of total intracellular antibody accumulation during the cell cycle is very similar to the previously described pattern for total protein accumulation (Kromenaker & Srienc 1991). The relative mean rate of heavy chain accumulation during the S phase was approximately half the relative mean rate of light chain accumulation during this cell cycle phase. This indicates an unbalanced synthesis of heavy and light chains that becomes most pronounced during this cell cycle phase. The nonproducer cells have on average an intracellular light chain content that is 42% lower than that of the producer cells. The nonproducer cells in the G₁ phase with low light chain content did not have a significantly higher rate of light chain accumulation relative to other G₁ phase nonproducer cells. This is in sharp contrast to what was observed for the G₁ phase producer cells. In addition, although the relative mean rate of accumulation of light chain was negative for G₂+M phase nonproducer cells, the magnitude of this relative mean rate was less than half that observed for the producer cells in this cell cycle phase. This suggests that the mechanisms that regulate the transport of fully assembled antibody molecules through the secretion pathway differ from those which regulate the secretion of free light chains. The results reported here indicate that there is a distinct pattern for the cell cycle dynamics of antibody synthesis and secretion in hybridomas. These results are consistent with a model for the dynamics of secretion which suggests that the rate of accumulation of secreted proteins will be greatest for newborn cells due to an interruption of the secretion pathway during mitosis.     

Cell cycle duration in antheridial filaments ofChara spp. (Characeae) with different genome size and heterochromatin content

The relationship between nuclear 1 C DNA content and cell cycle progression throughout successive stages of antheridial filaments were studied among five taxa ofChara: two dioecious species (n = 14):C. aspera (7.2 pg DNA),C. tomentosa (7.4 pg DNA), and three monoecious species (n = 28):C. vulgaris (13.5 pg DNA),C. fragilis (19.3 pg DNA), andC. contraria (19.6 pg DNA). With the use of double³H-thymidine labelling and morphometry a number of characteristics common to all of the investigated species were determined within the proliferative periods preceding spermiogenesis. These include: (1) simplified type of the cell cycle (S + G₂ + M), due to complete lack of G₁ intervals, (2) constant duration of S phase, (3) progressive shortening of G₂ + M periods, and (4) gradual reduction of cell lengths at successive mitotic divisions. Nucleotypic dependence was found between genome size and several time parameters estimated for consecutive stages of antheridial filaments: the higher the DNA C-value, the longer the cell cycles, their component phases, the total duration of the proliferative period, as well as the lower the rate of growth of interphase cells. Differential Giemsa staining of late G₂ phase nuclei revealed that the higher content of C-heterochromatin is connected with prolonged cell cycle durations in species with similar DNA C-values.