AB‐Bind: Antibody binding mutational database for computational affinity predictions

Antibodies (Abs) are a crucial component of the immune system and are often used as diagnostic and therapeutic agents. The need for high‐affinity and high‐specificity antibodies in research and medicine is driving the development of computational tools for accelerating antibody design and discovery. We report a diverse set of antibody binding data with accompanying structures that can be used to evaluate methods for modeling antibody interactions. Our Antibody‐Bind (AB‐Bind) database includes 1101 mutants with experimentally determined changes in binding free energies (ΔΔG) across 32 complexes. Using the AB‐Bind data set, we evaluated the performance of protein scoring potentials in their ability to predict changes in binding free energies upon mutagenesis. Numerical correlations between computed and observed ΔΔG values were low (r = 0.16–0.45), but the potentials exhibited predictive power for classifying variants as improved vs weakened binders. Performance was evaluated using the area under the curve (AUC) for receiver operator characteristic (ROC) curves; the highest AUC values for 527 mutants with |ΔΔG| > 1.0 kcal/mol were 0.81, 0.87, and 0.88 using STATIUM, FoldX, and Discovery Studio scoring potentials, respectively. Some methods could also enrich for variants with improved binding affinity; FoldX and Discovery Studio were able to correctly rank 42% and 30%, respectively, of the 80 most improved binders (those with ΔΔG < −1.0 kcal/mol) in the top 5% of the database. This modest predictive performance has value but demonstrates the continuing need to develop and improve protein energy functions for affinity prediction.     

Expression of HBcAg mutant with long internal deletion in Saccharomyces cerevisiae and observation of its self-assembly particles by atomic force microscopy (AFM)

An internally truncated C gene of adr hepatitis B virus core antigen with long internal deletion (aa81–aa116) (ΔHBcAg with 36aa truncation) was expressed in Saccharomyces cerevisiae and the products (ΔrHBcAg) were purified from a crude lysate of the yeast by three steps: Sephrose CL-4B chromatography, sucrose step-gradient ultracentrifugation and CsCl-isopycnic ultracentrifugation. Results of ELISA test and density analysis of CsCl-isopycnic ultracentrifugation indicated that the purified products (ΔrHBcAg protein) with HBeAg antigenicity mainly located at the densities of 1.23 g ml⁻¹. Observation and analysis of the purified ΔrHBcAg products by AFM indicated that the ΔrHBcAg (core) protein produced in S. cerevisiae could self-assemble into three or more size classes of core particles which exhibited a polymorphous distribution of ΔrHBcAg (core) particles. These different size classes of core particles mainly centred on the range whose mean diameter was from 10 nm to 48 nm, especially on the position of 11 nm, 15.6 nm and the range from 27 nm to 41 nm, respectively. Furthermore, the most number of core particles mainly centred on the range whose mean diameter was from 27 nm to 41 nm. These results above indicated that the truncated internal long fragment (aa81–aa116) probably had no effect on self-assembly of the HBcAg core particles which implied the internal length fragment (aa81–aa116) was not the sole domain for self-assembly of HBcAg dimer or the truncated HBcAg protein subunit formed the fresh interactive domain with each other. These initial results above by AFM analysis were very important for further research on the self-assembly, ultrastructure, subunit interaction and core internal deletion mutant (CIDM) function of HBcAg core particles.     

Benchmarking protein–protein interface predictions: Why you should care about protein size

A number of predictive methods have been developed to predict protein–protein binding sites. Each new method is traditionally benchmarked using sets of protein structures of various sizes, and global statistics are used to assess the quality of the prediction. Little attention has been paid to the potential bias due to protein size on these statistics. Indeed, small proteins involve proportionally more residues at interfaces than large ones. If a predictive method is biased toward small proteins, this can lead to an over‐estimation of its performance. Here, we investigate the bias due to the size effect when benchmarking protein‐protein interface prediction on the widely used docking benchmark 4.0. First, we simulate random scores that favor small proteins over large ones. Instead of the 0.5 AUC (Area Under the Curve) value expected by chance, these biased scores result in an AUC equal to 0.6 using hypergeometric distributions, and up to 0.65 using constant scores. We then use real prediction results to illustrate how to detect the size bias by shuffling, and subsequently correct it using a simple conversion of the scores into normalized ranks. In addition, we investigate the scores produced by eight published methods and show that they are all affected by the size effect, which can change their relative ranking. The size effect also has an impact on linear combination scores by modifying the relative contributions of each method. In the future, systematic corrections should be applied when benchmarking predictive methods using data sets with mixed protein sizes. Proteins 2014; 82:1444–1452. © 2014 Wiley Periodicals, Inc.     

Poly(A) sequences in Naegleria messenger RNA before and after initiation of differentiation : Absence of oligo(A)

The ameboid stage of the amebo-flagellate Naegleria gruberi was found to synthesize two size classes of polynucleotides resistant to digestion with a mixture of ribonuclease A and T1. These two size classes were present in both the nucleus and the cytoplasm. Cells differentiating into flagellates were found to lose a variable amount of the smaller, nuclease-resistant fragment while synthesizing only the larger nuclease-resistant class. The adenosine to AMP ratio of the larger nuclease-resistant fragment was compatible with a 3′-terminal poly(A) sequence of 87 nucleotides average length. The smaller nuclease-resistant fragment was found to be rich in AMP (44–49%) but contained a substantial amount of other nucleotides. The smaller fragment was heterogeneous in size with an average length of 10–12 nucleotides as estimated by its elution from a DEAE column. Fractionation of RNA on oligo(dT) cellulose demonstrated that the large and small nuclease-resistant fragments were on different RNA molecules. Only the large poly(A) sequence was present in either cytoplasmic or nuclear RNA which bound to oligo(dT) cellulose. On the other hand, only the small nuclease resistant fragment was found in the unbound RNA from either nuclei or cytoplasm.     

Monitoring detrital input and resuspension effects on sediment trap material using mineralogy and stable isotopes (δO and δC): the case of Lake Neuchâtel (Switzerland)

Isotopic analyses on bulk carbonates are considered a useful tool for palaeoclimatic reconstruction assuming calcite precipitation occurring at oxygen isotope equilibrium with local water and detrital carbonate input being absent or insignificant. We present results from Lake Neuchâtel (western Switzerland) that demonstrate equilibrium precipitation of calcite, except during high productivity periods, and the presence of detrital and resuspended calcite. Mineralogy, geochemistry and stable isotope values of Lake Neuchâtel trap sediments and adjacent rivers suspension were studied. Mineralogy of suspended matter in the major inflowing rivers documents an important contribution of detrital carbonates, predominantly calcite with minor amounts of dolomite and ankerite. Using mineralogical data, the quantity of allochthonous calcite can be estimated by comparing the ratio ankerite + dolomite/calcite + ankerite + dolomite in the inflowing rivers and in the traps. Material taken from sediment traps shows an evolution from practically pure endogenic calcite in summer (10–20% detrital material) to higher percentages of detrital material in winter (up to 20–40%). Reflecting these mineralogical variations, δ¹³C and δ¹⁸O values of calcite from sediment traps are more negative in summer than in winter times. Since no significant variations in isotopic composition of lake water were detected over one year, factors controlling oxygen isotopic composition of calcite in sediment traps are the precipitation temperature, and the percentage of resuspended and detrital calcite. Samples taken close to the river inflow generally have higher δ values than the others, confirming detrital influence. SEM and isotopic studies on different size fractions (<2, 2–6, 6–20, 20–60, >60 μm) of winter and summer samples allowed the recognition of resuspension and to separate new endogenic calcite from detrital calcite. Fractions>60 and <2 μm have the highest percentage of detritus. Fractions 2–6 and 6–20 μm are typical for the new endogenic calcite in summer, as given by calculations assuming isotopic equilibrium with local water. In winter such fractions show similar values than in summer, indicating resuspension. Using the isotopic composition of sediment traps material and of different size fractions, as well as the isotopic composition of lake water, the water temperature measurements and mineralogy, we re-evaluated the bulk carbonate potential for palaeoclimatic reconstruction in the presence of detrital and re-suspended calcite. This re-evaluation leads to the following conclusion: (1) the endogenic signal can be amplified by applying a particle-size separation, once the size of endogenic calcite is known from SEM study; (2) resuspended calcite does not alter the endogenic signal, but it lowers the time resolution; (3) detrital input decreases at increasing distances from the source, and it modifies the isotopic signal only when very abundant; (4) influence of detrital calcite on bulk sediment isotopic composition can be calculated.     

Measurement errors and regression to the mean cannot explain bias in average Ellenberg indicator values

Smart & Scott (2004, this is sue) criticized our paper (Wamelink et al. 2002) about the bias in average Ellenberg indicator values. Their main criticism concerns the method we used, regression analysis. They state the bias can be mimicked by the construction of an artificial data set and that regression analysis is not a suited tool to investigate underlying phenomena. Moreover they claim that the present bias is caused by the distribution of Ellenberg indicator values between syntaxa, instead of a bias in average Ellenberg indicator values per species. We show that their criticism of the use of regression analysis does not hold. We selected average Ellenberg values per vegetation group for several pH classes and applied an F‐test to determine whether or not the vegetation groups within each pH class differed significantly from each other. This was the case for all tested classes (P < 0.001). Moreover we simulated an artificial data set, of which the F‐test for varying measurement error could not explain the magnitude of the F‐value we found earlier. This indicates that the bias we found in average Ellenberg indicator values cannot be explained by measurement errors or by regression to the mean. In the end, Smart & Scott, as we did, come to the conclusion that there is a bias present and that separate regression lines per vegetation type are necessary, but the debate remains open on whether or not this is caused by the bias in Ellenberg indicator values per species.     

Correlations of amino acids in proteins

A correlation analysis among 20 amino acids is performed for four protein structural classes (, β, /β, and +β) in a total of 204 proteins. The correlation relationships among amino acids can be classified into the following four types: (1) strong positive correlation, (2) strong negative correlation, (3) weak correlation, and (4) no correlation. The correlation relationships are different for different proteins and are correlated with the features of their structural classes. The amino acids with the weak correlation relationship can be treated as the independent basis functions for the space where proteins are defined. The amino acids with large correlation coefficients are linear correlative with each other and they are not independent. The strong correlation among amino acids reflects their mutual constrained relationship, as exhibited by their relevant structural features. The information obtained through the correlation analysis is used for predicting protein structural classes and a better prediction quality is obtained than that by the simple geometry distance methods without taking into account the correlation effects.     

Late Ordovician (Turinian–Chatfieldian) carbon isotope excursions and their stratigraphic and paleoceanographic significance

Five positive carbon isotope excursions are reported from Platteville–Decorah strata in the Upper Mississippi Valley. All occur in subtidal carbonate strata, and are recognized in the Mifflin, Grand Detour, Quimbys Mill, Spechts Ferry, and Guttenberg intervals. The positive carbon isotope excursions are developed in a Platteville–Decorah succession in which background δ¹³C values increase upward from about −2‰ at the base to about 0‰ Vienna Pee Dee belemnite (VPDB) at the top. A regional north–south δ¹³C gradient, with lighter values to the north and heavier values to the south is also noted. Peak excursion δ¹³C values of up to +2.75 are reported from the Quimbys Mill excursion, and up to +2.6 from the Guttenberg excursion, although there are considerable local changes in the magnitudes of these events. The Quimbys Mill, Spechts Ferry, and Guttenberg carbon isotope excursions occur in units that are bounded by submarine disconformities, and completely starve out in deeper, more offshore areas. Closely spaced chemostratigraphic profiles of these sculpted, pyrite-impregnated hardground surfaces show that they are associated with very abrupt centimeter-scale negative δ¹³C shifts of up to several per mil, possibly resulting from the local diagenetic effects of incursions of euxinic bottom waters during marine flooding events.     

Gene Classification Using Codon Usage and Support Vector Machines

Abstract-- A novel approach for gene classification, which adopts codon usage bias as input feature vector for classification by support vector machines (SVM) is proposed. The DNA sequence is first converted to a 59-dimensional feature vector where each element corresponds to the relative synonymous usage frequency of a codon. As the input to the classifier is independent of sequence length and variance, our approach is useful when the sequences to be classified are of different lengths, a condition that homology-based methods tend to fail. The method is demonstrated by using 1,841 Human Leukocyte Antigen (HLA) sequences which are classified into two major classes: HLA-I and HLA-II; each major class is further subdivided into sub-groups of HLA-I and HLA-II molecules. Using codon usage frequencies, binary SVM achieved accuracy rate of 99.3% for HLA major class classification and multi-class SVM achieved accuracy rates of 99.73% and 98.38% for sub-class classification of HLA-I and HLA-II molecules, respectively. The results show that gene classification based on codon usage bias is consistent with the molecular structures and biological functions of HLA molecules.     

Analysis of neuropeptide Y-induced feeding: dissociation of Y1 and Y2 receptor effects on natural meal patterns.

To differentiate NPY receptor subtypes, Y₁ and Y₂, in terms of their impact on feeding behavior, the intact molecule NPY(1–36) and the 3 fragments, NPY(2–36), the Y₁ agonist [Leu³¹,Pro³⁴]NPY, and the Y₂ agonist NPY(13–36), were injected (100 pmol/0.3 μl) into the hypothalamic paraventricular nucleus (PVN) of freely feeding rats. A computer-automated data acquisition system was employed in these experiments to permit a detailed analysis of feeding over the 12-h nocturnal cycle, in animals maintained on pure macronutrient diets. The results demonstrate that: 1) NPY(1–36) potentiates feeding behavior, primarily carbohydrate ingestion, by increasing the size and duration of the first meal after injection, rather than by affecting meal number or feeding rate, suggesting that NPY acts through mechanisms of satiety. The potentiation of carbohydrate intake occurs in association with a suppression of protein intake, which is strongest during the second meal after injection and which further increases the proportion of carbohydrate in the diet. No changes in fat ingestion are seen. 2) NPY(2–36), with the N-terminal tyrosine residue deleted, is equally potent to NPY(1–36) in potentiating carbohydrate intake and increasing meal size; however, it is less selective than NPY(1–36), producing an additional, smaller increase in consumption of protein. 3) The stimulatory effect of these peptides on carbohydrate intake and meal size is similarly observed, with somewhat reduced potency, after PVN injection of the selective Y₁ agonist [Leu³¹,Pro³⁴]NPY which, like NPY(1–36), also reduces protein intake. 4) The Y₂ receptor agonist, NPY(13–36), causes a decrease in the ingestion of carbohydrate, a smaller decline in protein intake, and a reduction in meal size. It is proposed that hypothalamic Y₁ receptors mediate the stimulatory effect of NPY on carbohydrate intake and meal size, while Y₂ receptors have the opposite effect of suppressing carbohydrate intake, possibly by altering presynaptic release of monoamines known to influence nutrient ingestion.     

Renewable enzyme reactors based on beds of artificial gel antibodies

A novel approach is described for the synthesis of beds for enzyme reactors. The method is based on the use of artificial antibodies in the form of polyacrylamide gel particles with diameters around 0.1–0.3 mm. These gel particles mimic protein antibodies, raised in experimental animals, in the sense that they selectively recognize and adsorb only the protein present during the preparation of the “antibodies”. The gel antibodies have several advantages over conventional protein antibodies, which can be taken advantage of in the design of enzyme reactors; for instance, if upon prolonged use the immobilized enzyme loses its activity it can easily be replaced by an active enzyme, which is not possible when the enzyme is immobilized via a conventional protein antibody (a new bed with immobilized protein antibodies must be prepared); and equally or more remarkable: the enzyme can be applied in the form of a non-purified extract since the selectivity of the artificial gel antibodies is so high that they will “fish-out” the enzyme, but no other proteins in the extract. In addition, no preconcentration of the enzyme solution is required prior to the immobilization, since the enzyme is enriched at the top of the column upon the application. These unique properties make enzyme reactors based on artificial gel antibodies very attractive, also in process chromatography. The potential application range of the artificial gel antibodies is enormous since the same method for their synthesis can be used independent of the structure and the size of the “antigen”; for instance, renewable biosensors based on gel antibodies for the selective detection of protein biomarkers, as well as pathogenic viruses, bacteria, and spores (for instance Anthrax) should not be difficult to design.     

Metabolite and ionic composition of follicular fluid from different-sized follicles and their relationship to serum concentrations in dairy cows

Metabolic changes in blood serum may be reflected in the biochemical composition of follicular fluid and could indirectly influence oocyte quality. The purpose of this study was to examine the biochemical composition of follicular fluid harvested from different-sized follicles and its relationship with that of blood serum in dairy cattle. Following slaughter, blood samples were collected from dairy cows (n=30) and follicular fluid aspirated from three size classes of non-atretic follicles (<4 mm, 6–8 mm and >10 mm diameter). Samples remained independent between cows and between size classes within cows. Serum and follicular fluid samples were assayed using commercial clinical and photometric chemistry assays for ions (sodium, potassium and chloride) and metabolites (glucose, β-hydroxybutyrate (β-OHB), lactate, urea, total protein, triglycerides, non-esterified fatty acids (NEFA) and total cholesterol). Results showed that follicular fluid concentrations of glucose, β-OHB and total cholesterol increased from small to large follicles and decreased for potassium, chloride, lactate, urea and triglycerides. There was a significant concentration gradient for all variables between their levels in serum and follicular fluid (P<0.05). Significant correlations were observed for chloride (r=0.40), glucose (r=0.56), β-OHB (r=0.85), urea (r=0.95) and total protein (r=0.60) for all three follicle size classes and for triglycerides (r=0.43), NEFA (r=0.50) and total cholesterol (r=0.42) for large follicles (P<0.05). The results from the present study suggest that the oocyte and the granulosa cells of dairy cows grow and mature in a biochemical environment that changes from small to large follicles. Furthermore, the significant correlation between the composition of serum and follicular fluid for the above-mentioned metabolites suggests that metabolic changes in serum levels will be reflected in the follicular fluid and, therefore, may affect the quality of both the oocyte and the granulosa cells.     

Prediction of N-myristoylation modification of proteins by SVM

Attachment of a myristoyl group to NH(2)-terminus of a nascent protein among protein post-translational modification (PTM) is called myristoylation. The myristate moiety of proteins plays an important role for their biological functions, such as regulation of membrane binding (HIV-1 Gag) and enzyme activity (AMPK). Several predictors based on protein sequences alone are hitherto proposed. However, they produce a great number of false positive and false negative predictions; or they cannot be used for general purpose (i.e., taxon-specific); or threshold values of the decision rule of predictors need to be selected with cautiousness. Here, we present novel and taxon-free predictors based on protein primary structure. To identify myristoylated proteins accurately, we employ a widely used machinelearning algorithm, support vector machine (SVM). A series of SVM predictors are developed in the present study where various scales representing physicochemical and biological properties of amino acids (from the AAindex database) are used for numerical transformation of protein sequences. Of the predictors, the top ten achieve accuracies of >98% (the average value is 98.34%), and also the area under the ROC curve (AUC) values of >0.98. Compared with those of previous studies, the prediction accuracies are improved by about 3 to 4%.     

Productive performance of broiler chicks fed diets containing irradiated meat-bone meal

Experiments were carried out to study the changes in the values of feed efficiency (FE), total protein efficiency (TPE) and metabolizable energy efficiency (MEE) of broiler chicks fed during four age periods (14–21, 21–28, 28–35 and 35–42 days). Five experimental diets were similar in composition but different in the irradiation dose (0, 5, 10, 25 or 50 kGy) applied to the meat–bone meal content of each diet. The results indicated that feeding of broiler chicks on irradiated meat–bone meal (5–50 kGy) had no significant (P>0.05) effects on FE, TPE, MEE and body weight gain during the four experimental age periods. The average values of the FE (feed consumption/weight gain), TPE (weight gain/total protein consumption) and MEE (metabolizable energy consumption in MJ/kg gain) were 1.96, 2.59 and 23.13, respectively. The values of FE and MEE increased while TPE decreased significantly (P<0.05) with age. The pooled FE value was 1.60 during the 14–21 days of age and increased to 2.66 from 35–42 days of age. However, the TPE value was 3.01 during the 14–21-day age period and decreased to 1.82 over the 35–42-day age period. The energy consumption value to produce one kg of body weight increased during the 35–42-day period by 7.71–12.72 MJ/kg gain in comparison with that from the other experimental age periods. Weight gain rate decreased significantly (P<0.05) during the 35–42-day period (66 g/week/bird) when compared with the rate observed during the 14 through 35-day age period.     

Quantity and quality of seston in an impounded and a free-flowing river in Virginia,U.S.A.

Seston in the impounded North Anna River (NAR) was analyzed and compared to that in the free-flowing South Anna River (SAR) in Virginia, U.S.A. A wet filtration technique was used to separate seston into five size classes. The overall quantity of organic seston was much lower in the NAR than in the SAR. The seston in the NAR was composed of more living organisms, in particular zooplankters in the medium large (234–864 µm) and small (105–234 µm) size classes and diatoms and other algae in the fine (43–105 µm) and very fine (25–43 µm) size classes. The percentage of zooplankton declined sharply before reaching the downstream study site (32 km). The seston in the NAR tended to consist of slightly larger particles, but 80–85% of the seston in both rivers was in the ultrafine (0.45–25 µm) size class, which was almost entirely composed of detritus. One indication of seston food quality, the organic/inorganic ratio, was considerably higher for the medium large and small size classes in the NAR immediately below the dam and for the fine and very fine size classes farther downstream. Another indication of food quality, the usable caloric content, showed that the seston in the NAR contained considerably less total assimilable energy as far as 32 km downstream from the dam, but that the medium large and small size classes were rich in assimilable energy immediately below the dam because of zooplankton released from the reservoir. Thus, the overall quantity and quality of seston was lower in the NAR, but the quality of the seston, for at least a short distance below the dam, was higher in a well-defined size range that can be effectively utilized by certain filter feeders.     

Universal Pattern and Diverse Strengths of Successive Synonymous Codon Bias in Three Domains of Life, Particularly Among Prokaryotic Genomes

There has been significant progress in understanding the process of protein translation in recent years. One of the best examples is the discovery of usage bias in successive synonymous codons and its role in eukaryotic translation efficiency. We observed here a similar type of bias in the other two life domains, bacteria and archaea, although the bias strength was much smaller than in eukaryotes. Among 136 prokaryotic genomes, 98 were found to have significant bias from random use of successive synonymous codons with Z scores larger than three. Furthermore, significantly different bias strengths were found between prokaryotes grouped by various genomic or biochemical characteristics. Interestingly, the bias strength measured by a general Z score could be fitted well (R = 0.83, P < 10⁻¹⁵) by three genomic variables: genome size, G + C content, and tRNA gene number based on multiple linear regression. A different distribution of synonymous codon pairs between protein-coding genes and intergenic sequences suggests that bias is caused by translation selection. The present results indicate that protein translation is tuned by codon (pair) usage, and the intensity of the regulation is associated with genome size, tRNA gene number, and G + C content.     

Germination of Schizosaccharomyces pombe spores separated by zonal centrifugation

Spores from the fission yeast Schizosaccharomyces pombe (H90 strain) were separated from residual vegetative cells into distinct size classes by zonal density centrifugation. Spores were sized photographically and with a Coulter counter. The kinetics of germination were followed by time-lapse photomicrography. The duration of the pre-germination interval was size dependent. Large spores (˜50 μm³) germinated as early as 5 h after resuspension in nutrient media, smaller ones (˜20 μm³) did so at 11 h. The first cell division occurred 4–5 h later regardless of spore size. The large spores divided more synchronously as shown by the occurrence of peaks in the cell plate index at approximately one doubling time intervals.     

Estimating cladoceran birth rate: use of the egg age distribution to estimate mortality of ovigerous females and eggs

The birth rate of natural cladoceran populations can change rapidly (during 2–3 days), reflecting rapid changes in their environment. If the egg ratio is calculated on the basis of egg age distribution, the birth rate can be estimated at short sampling intervals (shorter than egg stage duration) by modified Paloheimo's (1974) formula. When female size structure and age of eggs in clutches at the beginning and the end of a sampling interval are known, death rates of ovigerous females and eggs in separate size classes can be determined and incorporated in birth rate estimates. All these methods have been employed using the data on the population of Diaphanosoma brahyurum from the lake Obsterno (North-Western Belarus) in July–August, 1992. The birth rate values computed by the proposed methods and Poloheimo's formula differed significantly in many cases. The accuracy of birth rate estimations from various calculation methods was tested using a computer simulation. The model contains the essential features of cladoceran life history: distinct egg, juvenile and adult stages, development of eggs and reproduction. The population was divided into 25 age classes, each of 1 day duration. Durations of the egg, juvenile and adult stages were set at 3, 6 and 20 days, respectively. The embryogenesis was divided into three egg stages, each of 1 day duration. Survivorship was set from 0.2 up to 1.0 for each age class. The survivorship and brood size were changed through each of five time intervals (days) that allowed to simulate an increase or reduction of population density. Fecundity, survivorship and egg stage duration remained constant during each of 5 days that assumed stability of an environment (this does not occur in nature). Nevertheless, the egg ratio, proportion of juveniles and birth rates were variable even under these circumstances. Computer simulations showed that Poloheimo's formula evaluates birth rate with the relative error of 62% and usually overestimates its values. We propose methods to decrease errors of birth rate estimations by 3.5–5.5 times.     

A quartz crystal microbalance cell biosensor: detection of microtubule alterations in living cells at nM nocodazole concentrations

The quartz crystal microbalance (QCM) was used to create a piezoelectric biosensor utilizing living endothelial cells (ECs) as the biological signal transduction element. ECs adhere to the hydrophilically treated gold QCM surface under growth media containing serum. At 24 h following cell addition, calibration curves were constructed relating the steady state Δf and ΔR shift values observed to the numbers of electronically counted cells requiring trypsinization to be removed from the surface. We then utilized this EC QCM biosensor for the detection of the effect of [nocodazole] on the steady state Δf and ΔR shift values. Nocodazole, a known microtubule binding drug, alters the cytoskeletal properties of living cells. At the doses used in these studies (0.11–15 μM), nocodazole, in a dose dependent fashion, causes the depolymerization of microtubules in living cells. This leads a monolayer of well spread ECs to gradually occupy a smaller area, lose cell to cell contact, exhibit actin stress fibers at the cell periphery and acquire a rounded cell shape. We observed the negative Δf shift values and the positive ΔR shift values to increase significantly in magnitude over a 4-h incubation period following nocodazole addition, in a dose dependent fashion, with a transition midpoint of 900 nM. Fluorescence microscopy of the ECs, fixed on the gold QCM surface and stained for actin, demonstrated that the shape and cytoskeleton of ECs were affected by as little as 330 nM nocodazole. These results indicate that the EC QCM biosensor can be used for the study of EC attachment and to detect EC cytoskeletal alterations. We suggest the potential of this cellular biosensor for the real time identification or screening of all classes of biologically active drugs or biological macromolecules that affect cellular attachment, regardless of their molecular mechanism of action.