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PubMed2026

Volumetric bone marrow cellularity (VBMC) assessment from routinely processed trephines using three-dimensional x-ray histology and gaussian peak modelling.

Objective.Bone marrow cellularity is routinely estimated from a small number of two-dimensional histology sections, making assessment sensitive to section representativeness, processing artefacts and observer interpretation. Three-dimensional (3D) x-ray histology (XRH), using x-ray computed microtomography (µCT), enables non-destructive whole-block imaging of trephine biopsies. This study evaluated whether XRH combined with Gaussian peak modelling could provide a pragmatic whole-block volumetric bone marrow cellularity (VBMC) estimate from formalin-fixed paraffin-embedded (FFPE) trephine biopsy blocks.Approach.Six routinely processed FFPE bone marrow trephine blocks were imaged using µCT-based XRH at ∼15 µm spatial resolution. VBMC was defined as the red-marrow (RM) fraction of the marrow soft-tissue compartment, RM/(RM + intra-biopsy wax), with wax serving as the volumetric proxy for adipocyte/yellow marrow space. Whole-volume greyscale histograms were modelled using a three-peak Gaussian approach representing intra-biopsy wax, RM and demineralised trabecular matrix. Peak-height and area-under-the-curve metrics were compared with whole-volume 3D segmentation and clinical two-dimensional (2D) cellularity estimates.Main Results.Gaussian peak modelling successfully approximated the segmented tissue-phase distributions. The peak-height-derived VBMC metric showed the closest agreement with whole-volume 3D segmentation, with an average absolute percentage difference of 9.3%, compared with 18.6% for clinical expert 2D cellularity estimates. The area-under-the-curve metric followed similar trends but consistently overestimated VBMC. Clinical 2D cellularity broadly followed whole-biopsy trends but showed one discordant case not explained by slice-position sampling alone. XRH also enabled unrestricted virtual reslicing and visualisation of sectioning-associated artefacts prior to further microtomy.Significance.Pre-sectioning XRH combined with Gaussian peak modelling provides a rapid, segmentation-free route to volumetric cellularity estimation from intact clinical FFPE trephine blocks. The approach supports objective whole-biopsy assessment while remaining compatible with routine histopathology workflows, reflecting the expected limitations of section-based visual estimation despite its role as the current clinical standard. In the near term, it could provide a non-disruptive adjunct to conventional 2D cellularity reporting, pending larger validation studies.

Imaging, Three-Dimensional↗

PubMed2005

Progressive thermal desorption of vapor mixtures from a preconcentrator with a porous metal foam internal architecture and variable thermal ramp rates.

A vapor preconcentrator has been designed with the porous polymer (Tenax) packed into a highly porous metal foam to facilitate thermal conductivity and temperature uniformity throughout the bed of the preconcentrator during heating. Vapors were desorbed using linear temperature programming from room temperature to a maximum temperature of 170 or 200 degrees C; the programmed duration of the thermal ramp was varied from 10 to 180 s. The partial separation of vapor mixtures that are thermally desorbed from the preconcentrator has been examined in terms of a metric for resolution, using methyl ethyl ketone, toluene, and dimethyl methylphosphonate as a test mixture. Vapors desorbed as a sequence of partially separated overlapping peaks, as observed with a polymer-coated flexural plate wave sensor. It was shown that vapor mixture resolution improved as the total time of the thermal ramp was extended from 30 to 120 s. In this way, the preconcentrator serves to act as a preseparator in addition to its usual functions for sampling, signal modulation, and improving sensitivity. Overlapping peaks were modeled, and peak areas were extracted using an exponentially modified Gaussian model. Peak areas were independent of the thermal ramp rate. Uses of such preconcentrators with multivariate detectors, such as sensor arrays, are discussed.

Journal Article↗

PubMed2005

Protein secondary structures (alpha-helix and beta-sheet) at a cellular level and protein fractions in relation to rumen degradation behaviours of protein: a new approach.

Studying the secondary structure of proteins leads to an understanding of the components that make up a whole protein, and such an understanding of the structure of the whole protein is often vital to understanding its digestive behaviour and nutritive value in animals. The main protein secondary structures are the alpha-helix and beta-sheet. The percentage of these two structures in protein secondary structures influences protein nutritive value, quality and digestive behaviour. A high percentage of beta-sheet structure may partly cause a low access to gastrointestinal digestive enzymes, which results in a low protein value. The objectives of the present study were to use advanced synchrotron-based Fourier transform IR (S-FTIR) microspectroscopy as a new approach to reveal the molecular chemistry of the protein secondary structures of feed tissues affected by heat-processing within intact tissue at a cellular level, and to quantify protein secondary structures using multicomponent peak modelling Gaussian and Lorentzian methods, in relation to protein digestive behaviours and nutritive value in the rumen, which was determined using the Cornell Net Carbohydrate Protein System. The synchrotron-based molecular chemistry research experiment was performed at the National Synchrotron Light Source at Brookhaven National Laboratory, US Department of Energy. The results showed that, with S-FTIR microspectroscopy, the molecular chemistry, ultrastructural chemical make-up and nutritive characteristics could be revealed at a high ultraspatial resolution ( approximately 10 microm). S-FTIR microspectroscopy revealed that the secondary structure of protein differed between raw and roasted golden flaxseeds in terms of the percentages and ratio of alpha-helixes and beta-sheets in the mid-IR range at the cellular level. By using multicomponent peak modelling, the results show that the roasting reduced (P<0.05) the percentage of alpha-helixes (from 47.1 % to 36.1 %: S-FTIR absorption intensity), increased the percentage of beta-sheets (from 37.2 % to 49.8 %: S-FTIR absorption intensity) and reduced the alpha-helix to beta-sheet ratio (from 0.3 to 0.7) in the golden flaxseeds, which indicated a negative effect of the roasting on protein values, utilisation and bioavailability. These results were proved by the Cornell Net Carbohydrate Protein System in situ animal trial, which also revealed that roasting increased the amount of protein bound to lignin, and well as of the Maillard reaction protein (both of which are poorly used by ruminants), and increased the level of indigestible and undegradable protein in ruminants. The present results demonstrate the potential of highly spatially resolved synchrotron-based infrared microspectroscopy to locate 'pure' protein in feed tissues, and reveal protein secondary structures and digestive behaviour, making a significant step forward in and an important contribution to protein nutritional research. Further study is needed to determine the sensitivities of protein secondary structures to various heat-processing conditions, and to quantify the relationship between protein secondary structures and the nutrient availability and digestive behaviour of various protein sources. Information from the present study arising from the synchrotron-based IR probing of the protein secondary structures of protein sources at the cellular level will be valuable as a guide to maintaining protein quality and predicting digestive behaviours.

Animal Feed↗

PubMedDate not supplied

Quantitative analysis of incomplete HPLC resolution of enantiomers. Fit of polarimetric detection for D- and L-phenylalanine to a gaussian function.

This report compares laser-based polarimetric and UV data for quantitating incompletely resolved enantiomers by HPLC. Using L- and D-phenylalanine as a working model, response data is shown across the entire detection region while emphasizing the regions at or near 100% L, 100% D and 50:50 L:D at resolutions between 0.4 and 1.4. In general, the poorer the resolution, the greater the improvement in detectability with the polarimeter when compared to UV detection. This is due to the inherent bipolar nature of the polarimetric signal, which creates a well-defined crossing point for integration of an enantiomeric pair. In our previous work, we described the improvement in measurement precision when applying a bipolar gaussian peak model to the raw chromatographic peak data. This study will measure the model's effect on improving accuracy. This study should be applicable to other chiroptical detection strategies that produce a bipolar signal for enantiomers, such as circular dichroism and circularly polarized luminescence.

Chromatography, High Pressure Liquid↗

PubMed2000

Effects of nicotine on regional cerebral glucose metabolism in awake resting tobacco smokers.

Eleven healthy tobacco smoking adult male volunteers of mixed race were tobacco abstinent overnight for this study. In each subject, positron emission tomographic images of regional cerebral metabolism of glucose with [18F]fluorodeoxyglucose were obtained in two conditions in the morning on different days: about 3min after approximately 1-2mg of nasal nicotine spray and after an equivalent volume of an active placebo spray of oleoresin of pepper in a random counterbalanced design. A Siemens/CTI 931/08-12 scanner with the capability of 15 horizontal brain slices was used. The images were further converted into a standard uniform brain format in which the mean data of all 11 subjects were obtained. Images were analysed in stereotactic coordinates using pixel-wise t statistics and a smoothed Gaussian model. Peak plasma nicotine levels varied three-fold and the areas under the curve(0-30min) varied seven-fold among the individual subjects. Nicotine caused a small overall reduction in global cerebral metabolism of glucose but, when the data were normalized, several brain regions showed relative increases in activity. Cerebral structures specifically activated by nicotine (nicotine minus pepper, Z score >4.0) included: left inferior frontal gyrus, left posterior cingulate gyrus and right thalamus. The visual cortex, including the right and left cuneus and left lateral occipito-temporal gyrus fusiformis, also showed an increase in regional cerebral metabolism of glucose with Z scores >3. 6. Structures with a decrease in regional cerebral metabolism of glucose (pepper minus nicotine) were the left insula and right inferior occipital gyrus, with Z scores >3.5. Especially important is the fact that the thalamus is activated by nicotine. This is consistent with the high density of nicotinic cholinoceptors in that brain region. However, not all brain regions affected by nicotine are known to have many nicotinic cholinoceptors. The results are discussed in relation to the cognitive effects of nicotine.

Administration, Intranasal↗

PubMed2005

Multicomponent peak modeling of protein secondary structures: comparison of gaussian with lorentzian analytical methods for plant feed and seed molecular biology and chemistry research.

The objective of this study was to compare Gaussian and Lorentzian multicomponent peak modeling methods in quantification of protein secondary structures of various plant seed and feed tissues within intact tissue at a cellular and subcellular level using the advanced synchrotron light sourced Fourier transform infrared (FT-IR) microspectroscopy (S-FTIR). This experiment was performed at the beamline U10B at the National Synchrotron Light Source (NSLS) in Brookhaven National Laboratory (BNL), U.S. Dept of Energy (NSLS-BNL, NY). The results show that in the comparison of the Gaussian and Lorentzian multi-peak modeling methods, the Gaussian method is more accurate for fitting multi-peak curves of protein secondary structures than the Lorentzian method, with higher modeling R(2) values (0.92 versus 0.89, P < 0.05). There were no large differences (P > 0.05) in the quantification of the relative percentage alpha-helices, beta-sheets, and others in protein secondary structures of the plant seed tissues, with averages of 30.2%, 40.4%, and 29.4%, respectively. However, there are significant differences (P < 0.05) in the quantification of the ratios of sheet alpha-helix (1.42 versus 1.60; SEM = 0.058) in protein secondary structures of the plant seed tissues. With synchrotron FT-IR microspectroscopy, the ultrastructural-chemical makeup and nutritive characteristics could be revealed at a high spatial resolution. Synchrotron-based FT-IR microspectroscopy revealed that the secondary structure of protein differed between the plant seed tissues in terms of relative percentage and ratio of protein secondary structures (alpha-helix and beta-sheet) within cellular dimensions. The results also show that the flaxseed tissues contained higher (P < 0.05) percentage alpha-helix (38.6 versus 24.0%) beta-sheet (45.3 versus 36.9%), lower (P < 0.05) percentage of other secondary structures (16.1% versus 39.0%), and higher (P < 0.05) ratios alpha-helix beta-sheet (0.90 versus 0.69) than the winterfat seed tissues. It must be mentioned that the relative percentages of protein secondary structure may not reflect the true secondary structure. However, the purpose of modeling the relative percentage of secondary structure was to detect the variety of differences among seed/feed/plant tissues and their relation to nutritive value and digestive behavior. The results demonstrate the potential of highly spatially resolved synchrotron-based FT-IR microspectroscopy to reveal protein secondary structures of the plant seed/feed tissues. Further study is needed to quantify the relationship between protein secondary structures and nutrient availability and digestive behavior of various varieties of plant seed tissues. Information from the infrared probing of protein secondary structures can be valuable as a guide to maintaining protein nutritive value and quality for animal and human use.

Algorithms↗

PubMed2002

Parabolic-Lorentzian modified Gaussian model for describing and deconvolving chromatographic peaks.

A new mathematical model for characterising skewed chromatographic peaks, which improves the previously reported polynomially modified Gaussian (PMG) model, is proposed. The model is a Gaussian based equation whose variance is a combined parabolic-Lorentzian function. The parabola accounts for the non-Gaussian shaped peak, whereas the Lorentzian function cancels the variance growth out of the elution region, which gives rise to a problematic baseline increase in the PMG model. The proposed parabolic-Lorentzian modified Gaussian (PLMG) model makes a correct description of peaks showing a wide range of asymmetry with positive and/or negative skewness. The new model is shown to give better fittings than other models as the Li, log-normal or Pap-Pápai models, which have a different mathematical basis. The model parameters are also related to peak properties as the skewness and kurtosis. The PLMG model is applied to the deconvolution of peaks in binary mixtures of structurally related compounds that are highly overlapped (retention times in min): oxytetracycline (9.00)--tetracycline (10.20), sulfathiazole (3.67)--sulfachloropyridazine (3.93), and sulfisoxazole (5.14)--sulfapyridine (5.24). The use of non-linear least-squares calibration in combination with the PLMG model gave superior results than the classical multiple linear least-squares and partial least-squares regressions. The proposed method takes into account run to run changes in retention time that occur along the injection of standards and samples, and the possible interactions that exist between the coeluting compounds. This decreases significantly the quantitation errors.

Chromatography↗

PubMed2001

A hybrid of exponential and gaussian functions as a simple model of asymmetric chromatographic peaks.

A hybrid of exponential and Gaussian functions is developed as a model of asymmetric peak profiles. This exponential-Gaussian hybrid function (EGH) is mathematically simple, numerically stable, and its parameters are readily determined by making graphical measurements and applying simple equations. Furthermore, the statistical moments of the EGH function can be accurately approximated (within+/-0.15% error) at any level of asymmetry using formulae that are easily programmed into a computer. These features of the EGH make it very easy to implement by most chromatographers. The EGH serves as a useful alternative to the exponentially modified Gaussian (EMG) for modeling slightly asymmetric peaks since the two models produce nearly the same profile at relatively low asymmetries. The EGH also serves as an addition to the extensive list of alternative models that are sometimes better than the EMG at describing highly asymmetric peaks. A comparison between EMG and EGH curves at various asymmetries is made by analysis of toluene, phenylalanine, and pyridine on a reversed-phase liquid chromatographic system.

Chromatography↗

PubMed2005

Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals part II: peak model and deconvolution algorithms.

Several interlinked algorithms for peak deconvolution by non-linear regression are presented. These procedures, together with the peak detection methods outlined in Part I, have allowed the implementation of an automatic method able to process multi-overlapped signals, requiring little user interaction. A criterion based on the evaluation of the multivariate selectivity of the chromatographic signal is used to auto-select the most efficient deconvolution procedure for each chromatographic situation. In this way, non-optimal local solutions are avoided in cases of high overlap, and short computation times are obtained in situations of high resolution. A new algorithm, fitting both the original signal and the second derivatives is proved to avoid local optima in intermediate coelution situations. This allows achieving the global optimum without the need of background knowledge by the user. A previously reported peak model, a Gaussian with a polynomial standard deviation whose complexity can be modulated to enhance the fitting quality, was applied. However, the original formulation was modified to account baseline outside the peak region. Also, the optimal model complexity was auto-selected via error propagation theory. The method is able to process simultaneously several related chromatograms. The software was tested with both simulated and experimental chromatograms obtained with monolithic silica columns.

Algorithms↗

PubMed2005

Deconvolution of overlapped peaks based on the exponentially modified Gaussian model in comprehensive two-dimensional gas chromatography.

Comprehensive two-dimensional gas chromatography (GC x GC) has attracted much attention for the analysis of complex samples. Even with a large peak capacity in GC x GC, peak overlapping is often met. In this paper, a new method was developed to resolve overlapped peaks based on the mass conservation and the exponentially modified Gaussian (EMG) model. Linear relationships between the calculated sigma, tau of primary peaks with the corresponding retention time (tR) were obtained, and the correlation coefficients were over 0.99. Based on such relationships, the elution profile of each compound in overlapped peaks could be simulated, even for the peak never separated on the second-dimension. The proposed method has proven to offer more accurate peak area than the general data processing method.

Chromatography, Gas↗

PubMed1990

Accuracy of peak deconvolution algorithms within chromatographic integrators.

The soundness of present-day algorithms to deconvolve overlapping skewed peaks was investigated. From simulated studies based on the exponentially modified Gaussian model (EMG), chromatographic peak area inaccuracies for unresolved peaks are presented for the two deconvolution methods, the tangent skim and the perpendicular drop method. These inherent inaccuracies, in many cases exceeding 50%, are much greater than those calculated from ideal Gaussian profiles. Multiple linear regression (MLR) was used to build models that predict the relative error for either peak deconvolution method. MLR also provided a means for determining influential independent variables, defining the required chromatographic relationships needed for prediction. Once forecasted errors for both methods are calculated, selection of either peak deconvolution method can be made by minimum errors. These selection boundaries are contrasted to method selection criteria of present data systems' algorithms.

Algorithms↗

PubMed1993

Multiwavelength analysis of the kinetics of reduction of cytochrome aa3 by cytochrome c.

Some new approaches to the kinetic study of the reduction of cytochrome aa3 by cytochrome c are presented. The primary innovations are the use of a spectrometer which can acquire multiwavelength data as fast as every 10 microseconds, and the application of a variety of analytical methods which can utilize simultaneously all of the time-resolved spectral data. These techniques include singular value decomposition (SVD), deconvolutions based on pure Gaussian models for absorption peaks, deconvolutions based on isolated absorption spectra for the pure components, and simulations of SVD-deduced and actual experimental difference spectra. The reduction characteristics of the anaerobic resting enzyme can be distinguished from those of pulsed forms. In the former case, only two electrons can be bound by cytochrome aa3, whereas in the latter case complete reduction of the enzyme is achieved.

Animals↗

PubMed2006

Model fitting in two dimensions to small angle diffraction patterns from soft tissue.

In our research programme small angle x-ray scattering (SAXS) is used to provide information on the axial arrangement of collagen molecules as well as data about the state of other components of the extra cellular matrix (ECM) in human tissues. Derivation of parameters to describe and simplify the data is required for much of the SAXS patterns analysis. A method is presented here to achieve function fitting to collagen diffraction peaks along with a representation of the underlying diffuse scatter. A simple model was used which proved reliable in fitting a variety of 2D diffraction patterns. The logarithm of the scatter intensity over the area of the scatter image was taken to reduce the range and improve fitting accuracy. Our model was then used to fit the log data. The model consisted of a radial exponential diffuse scatter component added to a specified number of Gaussian peaks. In 2D the peak model is toroidal, each component being rotated about a common specified centre. Initial search parameters from a 1D averaged sector were supplied to the iterative 2D fitting routine. With the aid of data weighting and basic wavelet filtering, successful and reliable fitting of a specified 2D model to real data is achievable. The process is easily automated. Multiple SAXS patterns can be fitted without operator intervention. As described the model is simple enough to converge rapidly and yet allows image data to be parameterized to a form suitable for extracting the requisite information. The fitting method is flexible enough to be extended to achieve a more comprehensive and complex pattern fitting in two dimensions if this turns out to be necessary. It is our intention to implement orientation distribution functions in the near future by including an angular scaling factor.

Animals↗

PubMed2004

Prediction of peak shape as a function of retention in reversed-phase liquid chromatography.

Optimisation of the resolution of multicomponent samples in HPLC is usually carried out by changing the elution conditions and considering the variation in retention of the analytes, to which a standard peak shape is assigned. However, the change in peak shape with the composition of the mobile phase can ruin the optimisation process, yielding unexpected overlaps in the experimental chromatograms for the predicted optimum, especially for complex mixtures. The possibility of modelling peak shape, in addition to peak position, is therefore attractive. A simple modified-Gaussian model with a parabolic variance, which is a function of conventional experimental parameters: retention time (tR), peak height (H0), standard deviation at the peak maximum (sigma0), and left (A) and right (B) halfwidths, is proposed. The model is a simplification of a previous equation proposed in our laboratory. Linear and parabolic relationships were found between the peak shape parameters (sigma0), A and B) and tR, with a mean relative error of 1-5% in most cases. This error was partially due to variations in peak position and shape among injections, which in some cases were above 2%. Correlations between (sigma0, A and B) and the retention time, which is easily modelled as a function of mobile phase composition, allowed a simple and reliable prediction of chromatographic peaks. A parameter that depends on the slopes of the linear relationships for A and B versus tR is also proposed to evaluate column efficiency. The modified-Gaussian model was used to describe the peaks of six diuretics of diverse acid-base behaviour and polarity, which were eluted with 15 mobile phases where the composition was varied between 30 and 50% (v/v) acetonitrile and the pH between 3 and 7.

Chromatography, Liquid↗

PubMed2005

A new mathematical function for describing electrophoretic peaks.

A new model is proposed for characterizing skewed electrophoretic peaks, which is a combination of leading and trailing edge functions, empirically modified to get a rapid recovery of the baseline. The peak model is a sum of square roots and is called thereby "combined square roots (CSR) model". The flexibility of the model was checked on theoretical and experimental peaks with asymmetries in the range of 0-10 (expressed as the ratio of the distance between the center and the trailing edge, and the center and the leading edge of the chromatographic peak, measured at 10% of peak height). Excellent fits were found in all cases. The new model was compared with other three models that have shown good performance in modelling chromatographic peaks: the empirically transformed Gaussian, the parabolic Lorentzian-modified Gaussian, and the Haarhoff-van der Linde function. The latter model was proposed recently to describe electrophoretic peaks. The CSR model offered the highest flexibility to describe electrophoretic peak profiles, even those extremely asymmetrical with long tails. The new function has the advantage of using measurable parameters that allow the direct estimation of peak areas, which is useful for quantitative purposes.

Electrophoresis↗

PubMed2004

Temporally convoluted Gaussian equations for chromatographic peaks.

Both spatial and temporal peaks that are produced by the discrete parcel model can be mathematically approximated by Gaussian functions, but the transformation from a spatial pattern to a temporal image requires a convolution treatment. A first-order convolution is given for temporal peaks under a linear isotherm, whereas a second-order convolution is proposed for those under non-linear isotherms. Numerical tests show that the peak shapes generated by the proposed temporally convoluted Gaussian equations (TCG) match perfectly with those obtained by the discrete parcel model. Although the full TCG equation may be quite complicated, it can be made easier by a recursion calculation technique, and a group of peak curves can be plotted simultaneously on computer worksheet. The results also suggest that the temporal distortion effect should be predominately considered, in addition to those known-to-exist spatial effects, for explaining the peak asymmetry.

Chromatography↗

PubMed2006

[Analyzing the effect of field frequencies on reconstructive accuracy of rebuilt field with spectroscopy].

The field to be reconstructed was simulated with numerical simulation technique. The effect of a three-dimensional field's characteristics, especially, its frequency components, on the reconstructive accuracy was discussed with spectroscopy. A double-peaked field model was built with Gaussian function, and its frequency components were analyzed by Fourier transform. With algebraic reconstruction technique, the model field was reconstructed. The reconstructed field was analyzed with many error indexes. As a result, the reconstructed field was similar to the model one in respect of the position, pointing and shape of the peaks, but the heights of the peaks were shorter than those of corresponding ones in the model. The border of the reconstructive field showed obvious fluctuation. It was considered that the main causation of the reconstructive result was the filtering inserted in iterating process. To confirm this idea, the convergence factor, represented with A, of Gaussian function was changed from six to thirty in order to change the frequency components of the model field, and the same numerical simulation as the one for the first model field with A=18 was carried out for these new model ones consisting of different frequency. As a result, the idea proved to be right. At the same time, it was found that the characteristics of the field at the edge of the reconstructed zone had a deeper effect on the reconstructive accuracy. When the precondition that the field edge approximated to zero could no longer existed, the reconstructive accuracy declined, and furthermore, it would make iterating process divergent. From all the above, the characteristics of the field at the edge should draw much attention when we reconstruct a field with Algebraic reconstruction technique.

English Abstract↗

PubMed2006

Identification and separation of DNA mixtures using peak area information.

We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic identification problems involving DNA mixture traces using quantitative peak area information. Peak area is modelled with conditional Gaussian distributions. The expert system can be used for ascertaining whether individuals, whose profiles have been measured, have contributed to the mixture. It can also be used to predict DNA profiles of unknown contributors by separating the mixture into its individual components. The potential of our probabilistic methodology is illustrated on case data examples and compared with alternative approaches. The advantages are that identification and separation issues can be handled in a unified way within a single probabilistic model and the uncertainty associated with the analysis is quantified. Further work, required to bring the methodology to a point where it could be applied to the routine analysis of casework, is discussed.

DNA↗