The first 142 amino acids of glutamate decarboxylase do not contribute to epitopes recognized by autoantibodies associated with Type 1 diabetes.

AIMS: Glutamate decarboxylase (GAD) antibodies are the most widely used predictive marker for Type 1 diabetes, but many individuals currently found to be GAD antibody-positive are unlikely to develop diabetes. We have shown previously that radioimmunoassays using N-terminally truncated 35 S-GAD65 (96-585) offer better disease specificity with similar sensitivity to full-length 35 S-GAD65 (1-585). To determine whether assay performance could be improved further, we evaluated a more radically truncated 35 S-GAD65 (143-585) radiolabel. METHODS: Samples from people with recent-onset Type 1 diabetes (n = 157) and their first-degree relatives (n = 745) from the Bart's-Oxford family study of childhood diabetes were measured for GAD antibodies using 35 S-labelled GAD65 (143-585). These were screened previously using a local radioimmunoassay with 35 S-GAD65 (1-585). A subset was also tested by enzyme-linked immunosorbent assay (ELISA), which performs well in international workshops, but requires 10 times more serum. Results were compared with GAD antibody measurements using 35 S-GAD65 (1-585) and 35 S-GAD65 (96-585). RESULTS: Sensitivity of GAD antibody measurement was maintained using 35 S-GAD65 (143-585) compared with 35 S-GAD65 (1-585) and 35 S-GAD65 (96-585). Specificity for Type 1 diabetes was improved compared with 35 S-GAD65 (1-585), but was similar to 35 S-GAD65 (96-585). Relatives found to be GAD antibody-positive using these truncated labels were at increased risk of diabetes progression within 15 years, compared with those positive for GAD(1-585) antibody only, and at similar risk to those found GAD antibody-positive by ELISA. CONCLUSIONS: The first 142 amino acids of GAD65 do not contribute to epitopes recognized by Type 1 diabetes-associated GAD antibodies. Low-volume radioimmunoassays using N-terminally truncated 35 S-GAD65 are more specific than those using full-length GAD65 and offer practical alternatives to the GAD antibody ELISA for identifying children at increased risk of Type 1 diabetes.

Modeling the Iatrogenic Pancreatic Cancer Risk After Islet Autotransplantation in Mouse.

Iatrogenic pancreatic cancer metastasis after islet infusion is a potential risk of islet autotransplantation performed after pancreatectomy. To model this risk, islets and/or pancreatic exocrine clusters obtained from a genetically engineered mouse model for pancreatic ductal adenocarcinoma (the LSL-KrasG12D/+ ;LSL-Trp53R172H/+ ;Pdx-1-Cre, termed KPC mouse) were transplanted via the portal vein in syngeneic wild type (WT) severely diabetic recipients in the following treatment groups: group A (n = 11) received KPC exocrine clusters in volume equal to 250 islet equivalents (IEQs); group B (n = 12) received 250 WT IEQs mixed with KPC exocrine clusters (1:1 volume ratio); group C (n = 5) received 250 KPC IEQs, and group D (n = 7) received 250 WT IEQs. The incidence of hepatic metastasis was assessed by magnetic resonance imaging and histology over the 13 months of follow-up. Overall survival was not different in the four groups. No mice developed liver metastases during the follow-up. Two mice developed spontaneous tumors: a liver hepatocellular tumor in group A and a malignant lymphoma in group D. Islets and/or exocrine clusters obtained by KPC mouse, a model that develops pancreatic cancer with 100% penetrance, do not retain the same risk of tumor development when transplanted via the portal vein in a syngeneic diabetic recipient.

Forecasting the growth of multicell tumour spheroids: implications for the dynamic growth of solid tumours.

The growth dynamics of multicell tumour spheroids (MTS) were analysed by means of mathematical techniques derived from signal processing theory. Volume vs. time trajectories of individual spheroids were fitted with the Gompertz growth equation and the residuals (i.e. experimental volume determinations minus calculated values by fitting) were analysed by fast fourier transform and power spectrum. Residuals were not randomly distributed around calculated growth trajectories demonstrating that the Gompertz model partially approximates the growth kinetics of three-dimensional tumour cell aggregates. Power spectra decreased with increasing frequency following a 1/f(delta) power-law. Our findings suggest the existence of a source of 'internal' variability driving the time-evolution of MTS growth. Based on these observations, a new stochastic Gompertzian-like mathematical model was developed which allowed us to forecast the growth of MTS. In this model, white noise is additively superimposed to the trend described by the Gompertz growth equation and integrated to mimic the observed intrinsic variability of MTS growth. A correlation was found between the intensity of the added noise and the particular upper limit of volume size reached by each spheroid within two MTS populations obtained with two different cell lines. The dynamic forces generating the growth variability of three-dimensional tumour cell aggregates also determine the fate of spheroid growth with a strong predictive significance. These findings suggest a new approach to measure tumour growth potential.

Oscillating growth patterns of multicellular tumour spheroids.

The growth kinetics of 9L (rat glioblastoma cell line) and U118 (human glioblastoma cell line) multicellular tumour spheroids (MTS) have been investigated by non-linear least square fitting of individual growth curves with the Gompertz growth equation and power spectrum analysis of residuals. Residuals were not randomly distributed around calculated growth trajectories. At least one main frequency was found for all analysed MTS growth curves, demonstrating the existence of time-dependent periodic fluctuations of MTS volume dimensions. Similar periodic oscillations of MTS volume dimensions were also observed for MTS generated using cloned 9L cells. However, we found significant differences in the growth kinetics of MTS obtained with cloned cells if compared to the growth kinetics of MTS obtained with polyclonal cells. Our findings demonstrate that the growth patterns of three-dimensional tumour cell cultures are more complex than has been previously predicted using traditional continuous growth models.

LH and FSH secretory responses to GnRH in normal individuals: a non-parametric deconvolution approach.

OBJECTIVE: To reconstruct the instantaneous secretion rate (ISR) of LH and FSH after GnRH administration in normal volunteers using non-parametric deconvolution, and to derive a direct integration formula to evaluate the amount of LH and FSH secreted during the first 60 min after the stimulus. DESIGN AND METHODS: First, the deconvolution method was validated in vivo by reconstructing doses ranging from 7.5 IU to 75 IU injected in three healthy adult volunteers whose endogenous LH had previously been downregulated by pretreating them, 3-4 weeks earlier, with 3.75 mg GnRH agonist i.m. Then, 40 healthy adult male volunteers were tested with a single 100 microg GnRH bolus, administered at 0 min. LH and FSH concentrations were determined at -30, 0, 15, 30, 45, 60, 90, and 120 min. RESULTS AND CONCLUSIONS: The validation study, conducted over a 10-fold range of doses, demonstrated that non-parametric deconvolution provided a reasonably accurate estimate of the amount of hormone entering the circulation. Applying deconvolution to the LH and FSH responses to GnRH, the ISRs of both hormones were shown to have a similar pattern, with a clearly delimited pulse after the GnRH bolus. In conjunction with earlier analyses of estimates of GHRH-stimulated GH secretion, we conclude that secretagogues evoke discrete LH, FSH, and GH secretory bursts of about 60 min total duration, despite markedly unequal (glyco-)protein hormone half-lives (18-500 min). With respect to the assessment of total hormone release during the first 60 min after the stimulus, the integration formula provided a reliable approximation of the result obtained by deconvolution, and had a negligible dependence on the samples at times 90 and 120 min.

Surface mechanomyogram reflects muscle fibres twitches summation.

The aim of this work is to define the pattern of summation of the muscle fibre twitches in the surface mechanomyogram (MMG) generation process. For this purpose, two groups of muscle fibres of the extensor digitorum communis (EDC) were stimulated using needle electrodes. To these two artificial (because made by different muscle fibre types) motor units (MU1 and MU2), we administered: (a) separate stimulations: 3 and 9 Hz (MU1), 8 and 20 Hz (MU2) for 5 s; (b) simultaneous stimulation: 3 Hz (MU1) + 8 Hz (MU2); 9 Hz (MU1) + 20 Hz (MU2) for 5 s. The mechanomyograms, recorded during separate stimulation of MU1 and MU2, were linearly summated for the generation of a mechanomyographic signal to be compared with the one detected during (b) stimulation procedure. The bispectrum and the bicoherence of the generated MMG (MMGg) and of the MMG recorded during simultaneous (MMGs) stimulation were calculated for the detection of the quadratic non-linearity in the system responses. It was found that the MMGg and MMGs presented difference in the bispectrum and bicoherence index only when the 9-20 Hz stimulation pair was considered In conclusion, our data indicate that the MMG derives from the summation of the active muscle fibres twitches and that the latter is linear only for very low firing rates. This is to be carefully considered when studies on MMG modelling will be undertaken.

Linear and nonlinear techniques for the deconvolution of hormone time-series.

Pulsatile hormone secretion is usually investigated by measuring hormone concentration in samples of peripheral plasma. In this paper, the deconvolution of hormone time-series to reconstruct the instantaneous secretion rate of glands is considered. Various techniques are discussed and compared in order to overcome the ill-conditioning of the problem and reduce the computational burden. In particular, linear techniques based on least squares, maximum a posteriori (MAP) estimation, and Wiener filtering are compared. A new nonlinear MAP estimator that keeps into account the non-Gaussian distribution of the unknown signal is worked out and shown to yield the best results. The performances of the algorithms are tested on simulated time-series as well as on series of Luteinizing Hormone (LH).

Topographic mapping of single sweep evoked potentials in the brain.

Single trial analysis of brain-evoked potentials via stochastic parametric identification and filtering is here extended to multichannel recordings, leading to the topographic mapping of the brain activity elicited by a single stimulus, instead of the usual averaged mapping. The temporal dynamics of the subsequent sweeps in the protocol of a neurophysiologic experiment can thus be recovered and quantified also on its spatial characteristic.

Deconvolution of infrequently sampled data for the estimation of growth hormone secretion.

In this paper, the deconvolution of infrequently and nonuniformly sampled data is addressed. A nonparametric technique is worked out that provides a smooth estimate of the unknown input signal and takes into account nonnegativity constraints. In spite of the size of the problem, efficient algorithms for solving the constrained optimization problem and computing confidence intervals are proposed. The new technique is used to estimate growth hormone (GH) secretion after repeated GH-releasing hormone (GHRH) administration from samples of blood concentration.

A model for the cortico-cortical neural interaction in multisensory-evoked potentials.

This paper addresses the methodological problem of enhancing selective responses from the central nervous system when two (or more) different sensorial stimuli are simultaneously presented to the subject. In particular, contemporaneous visual and somato-sensory stimulation is considered and a model of signal and noise interaction is developed for the processing of the evoked responses. An ARXX parametric model (AutoRegressive with two eXogenous inputs) is introduced and a least squares algorithm is used to determine the selective response of the two neural systems from the overall evoked response. Such an analysis may be also carried out on a sweep-by-sweep basis. Applications of this method are the following ones: i) modeling of multisensory potentials; ii) description of facilitation or defacilitation phenomena in multitasking experiments; iii) analysis of cortico-cortical neural interactions.

Analysis of single trial movement-related brain macropotential.

A parametric method of identification of movement-related brain macropotentials on a single trial basis through an ARX (autoregressive with exogenous inputs) algorithm is presented. The basic estimation of the information contained in the single trial is taken from an average carried out on a sufficient number of trials, while the noise sources, EEG and EOG are characterized as exogenous inputs in the model. The simulations as well as the experimental results confirm the capability of the model to drastically improve the signal/noise ratio in each single trial and to satisfactorily identify the contributions of signal and noise in the overall recording. This way, using the same algorithm, a particularly efficient reduction of ocular artifacts is also achieved. The movement-related brain macropotentials recorded in three subjects show a high degree of variability from trial and this effect seems to be related to programming processes and evaluation of errors.

Sequential changes in mucosal immunity after hemorrhagic shock.

Immunoinflammatory responses after shock and major trauma are characterized by an early hyperinflammatory response and later by compensatory anti-inflammatory host mediator production. This late phase is associated with depressed immune function that has been causally linked with post-traumatic infectious complications and late organ failure. Gut barrier failure is noted in this setting and may be an important source of nosocomial infections and organ failure. Secretory immunoglobulin A (sIgA) is the predominant immunoglobin at mucosal surfaces and is difficult to quantify in luminal secretions. Attempts to normalize sIgA concentrations may not be accurate and/or may not be applicable in vivo. A method using mucosal immunization with cholera toxin (ChT) to normalize gut sIgA levels was used to assess serial changes in sIgA after hemorrhagic shock (HS) in rodents. Total and anti-ChT sIgA levels were highly variable in both HS and sham animals. However, when normalized using the specific anti-ChT/total sIgA ratio, differences were clearly evident. This ratio was depressed between 3 and 10 days post-HS. The specific anti-ChT/total sIgA ratio is a reliable index of secretory antibody at gut luminal surfaces. Impaired mucosal immune function occurred in a time frame consistent with development of late nosocomial infections. This may be important mechanistically in the development of these infectious complications.

The effects of bacterial overgrowth and hemorrhagic shock on mucosal immunity.

Impairment in systemic and mucosal immune function is noted after hemorrhagic shock (HS). Overgrowth of gut microflora is common after shock insults and may act as a reservoir for intensive care unit-acquired infections and subsequent remote organ failure. Secretory immunoglobulin A (IgA), the principle immunoglobulin in intestinal secretions, is the first line of defense of mucosal surfaces. Although HS and gut bacterial overgrowth are often temporarily related, their combined effect on IgA is unknown and served as the basis for this study. After sham or HS, self-filling blind loops (SFBL) were created to affect bacterial overgrowth. Intestinal secretions were obtained 7 days later from SFBL and jejunal segments for quantitative culture. Gut washings were also obtained and secretory IgA levels determined by enzyme-linked immunosorbent assay. Bacterial overgrowth in the SFBL was associated with significant increases in IgA levels in the sham group only. IgA levels were depressed in both jejunal and SFBL segments in the HS group. Impaired humoral mucosal defense may be important mechanistically in the development of nosocomial infections and organ failure after HS, particularly with concurrent gut bacterial overgrowth.

Hemorrhagic shock impairs mucosal immunity to gut-derived antigens.

Secretory immunoglobulin A (sIgA) is the principal antibody protecting against pathogens in the respiratory tract and other mucosal surfaces. Nosocomial pneumonias are frequent after injury and critical illness and are often due to enteric pathogens. The aim of this study was to assess the relative effect of hemorrhagic shock (HS) on mucosal immunity at intestinal and respiratory mucosal sites. Fisher rats were immunized intragastrically with dinitrophenylated (DNP) Pneumococcus (Pn). Three weeks later, animals were subjected to sham treatment or HS. The animals were then rechallenged with DNP-Pn 1 or 3 days later. Animals were sacrificed 7 days later, and bronchoalveolar and gastric lavage was performed. Total and anti-DNP-specific sIgA were quantitated from these secretions by enzyme-linked immunosorbent assay. There was a significant decrease in DNP-Pn-specific sIgA at 72 hours after HS, which was not present in animals at 24 hours after HS. This was most profound in bronchoalveolar lavage specimens. We conclude that impaired mucosal defense against gut-derived antigens after HS may be important mechanistically for the development of posttraumatic pneumonia and other mucosally related infectious complications.

ARX filtering of single-sweep movement-related brain macropotentials in mono- and multi-channel recordings.

A technique of stochastic parametric identification and filtering is applied to the analysis of single-sweep event-related potentials. This procedure, called AutoRegressive with n eXogenous inputs (ARXn), models the recorded signal as the sum of n+1 signals: the background EEG activity, modeled as an autoregressive process driven by white noise, and n signals, one of which represents a filtered version of a reference signal carrying the average information contained in each sweep. The other (n-1) signals could represent various sources of noise (i.e., artifacts, EOG, etc.). An evaluation of the effects of both artifact suppression and accurate selection of the average signal on mono- or multi-channel scalp recordings is presented.

Linear spectral deconvolution of catabolic plasma concentration decay in dialysis.

Deconvolution can be a useful step in the process of modelling biological data, as it produces an overview of the information content of the data, as well as directions about the structure of the mathematical model able to describe the generating system. This paper concerns the application of a deconvolution technique, spectral analysis, to the modelling process of the concentrations of metabolites sampled in plasma during dialysis: the spectral analysis consists in linearly identifying the whole spectrum of multi-exponential decays, describing the compartmental nature of the process. The application to urea and creatinin time series provides a careful determination of the spectra of the exponential decays, thus giving interesting insight into the system kinetics: a sharp, slow decay (about 0.23 h-1 for urea and 0.17 h-1 for creatinin) affects all the subjects, whereas a variable set of smaller and faster components accounts for interpatient variability as well as for the multicompartmental nature of the process. The power ratio of the components is an index of the relative amount of volume in the related compartments. The identified spectra provide a description of the data that, although computed in a very simple way, is consistent with the results of the classical identification techniques previously applied in building compartmental models of dialysis.

Parametric method for the detection of inter- and intrasweep variability in VEP processing.

The paper introduces a Kalman filter procedure for the processing of single-sweep visual evoked potentials (VEPs). The identification of the filter coefficients is based on a model of signal and noise interaction which considers the generating process as the superposition of the true evoked response to an AR process (the background EEG) and a broader spectrum noise. Intersweep variability is thus evident on the filtered response and a functional parameter of the filter (VP(t), namely variability path) is proposed for the automatic determination of the latencies associated with the main peaks of the response. Finally, the time-variant algorithm allows the quantification of the intrasweep variability for possible interpretation of the physiological mechanism involved.

Estimating germinability of Plasmopara viticola oospores by means of neural networks.

Neural networks are trained to estimate the germination percentages of Plasmopara viticola oospores, overwintered in natural conditions in two viticultural areas in northern Italy, by using climatic (temperature and rainfall) data, as well as the previous germination measurement, as input variables. The 288 available patterns consist of a set of selected independent variables associated with the corresponding germination percentage. All 12 networks investigated converge to a non-linear relationship between the selected independent variables and oospore germination. The highest correlation coefficient (equal to 0.83) between the real and estimated germination percentages is obtained by considering, as input to the network, the climatic data (both temperature and rainfall) recorded during the 40 days before sampling and the germination percentage assessed in the germination assay carried out immediately before the present sampling.

Total and partial coherence analysis of spontaneous and evoked EEG by means of multi-variable autoregressive processing.

The joint use of total and partial coherence between pairs of EEGs simultaneously recorded in a standard set, is shown to enhance what is caused by direct correlation between cortical subsystems and what is instead related to the spread of the electromagnetic field. A multi-variable autoregressive approach is employed in the computation, giving results even for a very short time window, thus allowing coherence to be investigated at the main cortical latencies of evoked potentials. In particular, when a combined visual and somatosensory stimulation is applied, cortical interactions are captured in the frequency domain.

New compartmental model approach to dialysis.

Compartmental models are used for solving the problem of the control of dialysis therapy. The inadequacy of the existing monocompartmental model is faced, first with a careful analysis of the physiology of the system, then with a method focused on the construction of a new multicompartmental model. Moreover, impedance techniques allow us to solve the problem of measuring the total body water for each patient.