Blind Validation Tests Research Articles

A colorimetric, sensitive, rapid, and simple diagnostic kit for the HLB putative causal agent detection

Huanglongbing (HLB) is one of the most devastating diseases in citrus worldwide. The Gram-negative bacterial plant pathogen “Candidatus Liberibacter spp.” is phloem-limited and vectored by citrus psyllids. The species “Candidatus Liberibacter asiaticus” (C.Las) has been detected in Argentina, and its vector has been found in at least nine provinces. Early detection of C.Las is critical for a successful management of HLB disease. Currently, HLB molecular diagnosis is carried out by PCR, nested PCR, real-time PCR, or another combination of these techniques, which require purification of genomic DNA, sophisticated equipment, and highly trained personnel. We have developed a prototype of a sensitive colorimetric kit to detect C.Las based on the specific DNA isothermal amplification of this microorganism. The reaction buffer contains hydroxynaphthol blue (HNB), an indicator dye that turns from violet to blue/light blue when the DNA amplification reaction is positive. Similar sensitivity to visualize a positive reaction was observed between HNB loop-mediated isothermal amplification and agarose gel electrophoresis analysis. The detection of C.Las-infected plants was up to 8 ng of total infected plant genomic DNA, similar to quantitative PCR. A blind validation test of the prototype kit was performed with purified DNA extracted from healthy or C.Las-infected midrib plants. Our kit showed 100% concordance with the results of a gold-standard quantitative PCR technique applied by the Laboratorio de Biología Molecular de EEA Montecarlo. The analysis of samples, without DNA purification to detect C.Las, showed a similar sensitivity to the analysis of the same samples in which C.Las DNA was previously purified.

Multi-strut and empirical formula-based macro modeling for masonry infilled RC frames

It is widely accepted that infill walls play an important role in the structural response of buildings under seismic excitations. Disregarding their influences on the seismic design and evaluation of structures could be potentially dangerous. Therefore, a reliable numerical model is necessary. Because of its simplicity and efficiency, the equivalent strut model is the most widely used to represent infilled frames. In this study, a novel multi-strut macro model and associated empirical formulas for modeling infilled RC frames are proposed. The model was developed based on previous experimental observations. Fiber-section truss elements are used as the struts. All potential failure modes of the infill wall were considered by means of the equivalent stress–strain parameters of the struts. Empirical formulas for predicting these equivalent stress–strain parameters were developed and calibrated based on a comprehensive experimental database and regression analysis. Finally, blind validation tests of the proposed model and empirical formulas were performed to assess their reliability. Monotonic and cyclic load simulations of the infilled RC frames were carried out and compared with experimental results. The application of the proposed approach for both single-bay and multi-bay infilled frame simulations was examined.

Development and Validation of New Bouc–Wen Data-Driven Hysteresis Model for Masonry Infilled RC Frames

During the last years, several mechanics-based macromodels have been proposed to assess the cyclic response of infilled RC frames. However, the uncertainties behind the assumptions on damage and failure mechanisms compromise the reliability of such approaches. For this reason, this paper proposes a new data-driven hysteresis model for the cyclic response of infilled RC frames. The infill panel is schematized as a single-degree-of-freedom element, whose constitutive law is given by the proposed hysteresis model. The model combines a degrading Bouc–Wen element with a slip-lock element, which is introduced specifically to reproduce the pinching effect due to crack openings in the masonry panel. The parameters governing the model have clear physical meanings and are calibrated on the basis of an experimental data set of cyclic responses of single-story single-bay RC infilled frames. The calibrations are carried out by means of a genetic algorithm–based optimization. Analytical correlation laws linking the model parameters with geometric and mechanical properties of the RC infilled frame are proposed and validated by blind validation tests. Results show adequate accuracy of the model in reproducing the cyclic response of infilled frames characterized by significantly different geometrical and mechanical features. The model is defined by a smooth analytical hysteresis law, with great advantages regarding numerical stability and computational effort. This makes it suitable for dynamic and stochastic simulations.

Chemometric analysis on ATR-FT-IR spectra of spray paint samples for forensic purposes.

Forensic investigation of cases involving spray paints requires comparison of paint such as those recovered from graffiti with the references sample seized from the suspect's possession site. This study describes the use of Attenuated Total Reflectance Fourier Transform Infrared (ATR-FT-IR) spectroscopy for nondestructive analysis of 20 red spray paints of different manufactures, which could be encountered at a crime scene, particularly in case of vandalism. Spray paints could be encountered on a number of different substrates, and therefore, the samples were placed on simulated substrates and were analyzed in order to check the effect of substrates on sample analysis. Results showed that all samples could be successfully differentiated using ATR-FT-IR spectroscopy assisted with principal component analysis. Analysis of spray paints on a paper and fabric substrate resulted in poor spectra and hampered the comparative examination between the spray paint deposited on fabric/paper surface and the control sample. In case of sample deposited on cemented wall, the substrate got scraped out along with the sample and caused interferences in the spectrum. On the other hand, for sample deposited on the floor, gloves, metal, plastic, leather shoes, tile, wood, and hair substrates, all the significant peaks were observed to be present and hence it was concluded that comparative studies can be done between neat spray paint and spray paint deposited on the aforesaid substrates. Additionally, blind validation test was conducted and it resulted in linking the blind samples with the source or origin with 100% accuracy.

Forensic differentiation of amanita mushrooms using atr-ftir spectroscopy coupled with chemometrics

In mushroom poisoning cases, genus Amanita is responsible for majority of fatalities. Most of such cases are due to the accidental consumption of inedible mushrooms, but there is a high probability of their use forhomicidal purposes. Mushroom species can be identified based on the morphological features, however, in the field of forensic science,available exhibits are recovered in trace amounts, which pose a serious challenge before the forensic experts to analyse the samples in a non-destructive manner. In current work, ATR FT-IR spectroscopy has been used for the non-destructive identification and differentiation of six species of genus Amanita. To distinguish the selected mushroom species, chemometric tools like PCA and PLS-DA were applied. All samples were not successfully classified using the PCA model, therefore the PLS-DA model was applied to enhance the classification rate. PLS-DA model yielded a significant classification rate for the differentiation among the samples of different wild mushroom species. Furthermore, blind validation test was conducted and all unknown samples were classified accurately to their respective class. The obtained R-square value for PLS-DA model was 0.99 which is highly significant for the prediction accuracy.

Are flood damage models converging to “reality”? Lessons learnt from a blind test

Abstract. Effective flood risk management requires a realistic estimation of flood losses. However, available flood damage estimates are still characterized by significant levels of uncertainty, questioning the capacity of flood damage models to depict real damages. With a joint effort of eight international research groups, the objective of this study was to compare, in a blind-validation test, the performances of different models for the assessment of the direct flood damage to the residential sector at the building level (i.e. microscale). The test consisted of a common flood case study characterized by high availability of hazard and building data but with undisclosed information on observed losses in the implementation stage of the models. The nine selected models were chosen in order to guarantee a good mastery of the models by the research teams, variety of the modelling approaches, and heterogeneity of the original calibration context in relation to both hazard and vulnerability features. By avoiding possible biases in model implementation, this blind comparison provided more objective insights on the transferability of the models and on the reliability of their estimations, especially regarding the potentials of local and multivariable models. From another perspective, the exercise allowed us to increase awareness of strengths and limits of flood damage modelling, which are summarized in the paper in the form of take-home messages from a modeller's perspective.

Targeting humanitarian aid using administrative data: Model design and validation

We develop and assess the performance of an econometric prediction model that relies on administrative data held by international agencies to target over $380 million annually in unconditional cash transfers to Syrian refugees in Lebanon. Standard metrics of prediction accuracy suggest targeting using administrative data is comparable to a short-form Proxy Means Test, which requires a survey of the entire target population. We show that small differences in accuracy across approaches are largely attributable to a few data fields. These results are robust to a blind validation test performed on a random sample collected after the model derivation, as well as the type of estimator used for prediction. We discuss relative costs, which are likely to feature prominently when alternative approaches are considered in practice.

A faster and easier biodosimetry method based on calyculin A-induced premature chromosome condensation (PCC) by scoring excess objects

Dicentric analysis and the ring PCC assay as established biodosimetry methods both have limitations in the estimation of absorbed doses in suspected overexposure cases between 5 and 10 Gy. The proposed method based on calyculin A-induced PCC overcomes these limitations by scoring excess objects as the endpoint. This new scoring method can potentially serve as a faster and up-scalable approach that complements the existing methods with higher accuracy at different dose ranges. It can also potentially be performed by less skilled workers when no automated system is available in mass casualty emergency cases to assist with the triage of patients. Additionally, it offers the possibility to further reduce the sample size and PCC induction time. In this pilot study, a calibration curve for excess objects was constructed using the new scoring method for the first time and a blind validation test composed of three unknown doses was carried out. Almost all the dose estimates were within the 95% confidence limits of the actual test doses by scoring only 50–100 PCC spreads. This method was found to be more accurate than ring PCC for doses below 10 Gy.

A Simplified Calyculin A-Induced Premature Chromosome Condensation (PCC) Protocol for the Biodosimetric Analysis of High-Dose Exposure to Gamma Radiation.

Chemical-induced premature chromosome condensation (PCC) is an alternative biodosimetry method to the gold-standard dicentric analysis for ionizing radiation. However, existing literature shows great variations in the experimental protocols which, together with the different scoring criteria applied in individual studies, result in large discrepancies in the coefficients of the calibration curves. The current study is based on an extensive review of the peer-reviewed literature on the chemical-induced ring PCC (rPCC) assay for high-dose exposure. For the first time, a simplified yet effective protocol was developed and tested in an attempt to reduce the scoring time and to increase the accuracy of dose estimation. Briefly, the protein phosphatase inhibitor, calyculin A, was selected over okadaic acid for higher efficiency. Colcemid block was omitted and only G2-PCC cells were scored. Strict scoring criteria for total rings and hollow rings only were described to minimize the uncertainty resulting from scoring ring-like artefacts. It was found that ring aberrations followed a Poisson distribution and the dose-effect relationship favored a linear fit with an α value of 0.0499 ± 0.0028 Gy-1 for total rings and 0.0361 ± 0.0031 Gy-1 for hollow rings only. The calibration curves constructed by scoring ring aberrations were directly compared between the simplified calyculin A-induced PCC protocol and that of the cell fusion-induced PCC for high-dose exposure to gamma rays. The technical practicalities of these two methods were also compared; and our blind validation tests showed that both assays were feasible for high-dose γ-ray exposure assessment even when only hollow rings in 100 PCC spreads were scored.

Multispectral imaging for quality control of laboratory‐reared Anastrepha fraterculus (Diptera: Tephritidae) pupae

AbstractThe sterile insect technique (SIT) has been widely used to suppress several fruit fly species. In southern Brazil, millions of sterile flies of the South American fruit fly, Anastrepha fraterculus Wiedemann (Dipetra: Tephritidae), will be produced in a mass‐rearing facility called MOSCASUL to suppress wild populations from commercial apple orchards. In spite of standard rearing conditions, the quality of pupal batches can be inconsistent due to various factors. The quantification of poor quality material (e.g. empty pupae, dead pupae or larvae) is necessary to track down rearing issues, and pupal samples must be taken randomly and evaluated individually. To speed up the inspection of pupal samples by replacing the manual testing with the mechanized one, this study assessed a multispectral imaging (MSI) system to distinguish the variations in quality of A. fraterculus pupae and to quantify the variations based on reflectance patterns. Image acquisition and analyses were performed by the VideometerLab4 system on 7‐d‐old pupae by using 19 wavelengths ranging from 375 to 970 nm. The image representing the near infrared wavelength of 880 nm clearly distinguished among high‐quality pupae and the other four classes (i.e. low‐quality pupae, empty pupae, dead pupae and larvae). The blind validation test indicated that the MSI system can classify the fruit fly pupae with high accuracy. Therefore, MSI‐based classification of A. fraterculus pupae can be used for future pupal quality assessments of fruit flies in mass‐rearing facilities.

Model calibration and optimization of a post-combustion CO2 WAG pilot in a mature oil field

A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world's largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology, this is a challenging and novel application of CO2 enhanced oil recovery. The aim of this study is two-fold. First, to build a predictive dynamic model that incorporates the data acquired during the pilot operation. Second, to utilize this model to provide guidance for optimal design for a field-wide CO2 EOR operation.This study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. Next, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2.Sensitivity studies were conducted using the calibrated pilot model to evaluate the effects of various operational parameters. Finally, we performed a Design of Experiment based multi-objective optimization of the CO2 WAG processes using the influential operational parameters identified from the sensitivity analysis.

Targeting Humanitarian Aid Using Administrative Data: Model Design and Validation

We develop and assess the performance of an econometric targeting model for a large scale humanitarian aid program providing unconditional cash and food assistance to refugees in Lebanon. We use regularized linear regression to derive a prediction model for household expenditure based on demographic and background characteristics from administrative data that are routinely collected by humanitarian agencies. Standard metrics of prediction accuracy suggest this approach compares favorably to the commonly used scorecard Proxy Means Test, which requires a survey of the entire target population. We confirm these results through a blind validation test performed on a random sample collected after the model derivation.

A Global Empirical Model for Near‐Real‐Time Assessment of Seismically Induced Landslides

AbstractEarthquake‐triggered landslides are a significant hazard in seismically active regions, but our ability to assess the hazard they pose in near‐real‐time is limited. In this study, we present a new globally applicable model for seismically induced landslides based on the most comprehensive global data set available; we use 23 landslide inventories that span a range of earthquake magnitudes and climatic and tectonic settings. We use logistic regression to relate the presence and distribution of earthquake‐triggered landslides with spatially distributed estimates of ground shaking, topographic slope, lithology, land cover type, and a topographic index designed to estimate variability in soil wetness to provide an empirical model of landslide distribution. We tested over 100 combinations of independent predictor variables to find the best fitting model, using a diverse set of statistical tests. Blind validation tests show that the model accurately estimates the distribution of available landslide inventories. The results indicate that the model is reliable and stable, with high balanced accuracy (correctly versus incorrectly classified pixels) for the majority of test events. A cross‐validation analysis shows high balanced accuracy for a majority of events as well. By combining near‐real‐time estimates of ground shaking with globally available landslide susceptibility data, this model provides a tool to estimate the distribution of coseismic landslide hazard within minutes of the occurrence of any earthquake worldwide for which a U.S. Geological Survey ShakeMap is available.

Time-lapse reservoir property change estimation from seismic using machine learning

Time-lapse seismic analysis is an important tool in reservoir management, well planning, and reservoir model updating. Existing 4D close-the-loop methods utilize rock-physics models and simulation models, and typically work well in simple 4D cases such as water flood movement (where the primary change is the saturations), but they face challenges in reliably and quantitatively estimating 4D reservoir property changes when the reservoir dynamics are complex. We demonstrate a data-driven quantitative method that uses machine learning to leverage the inherent physics between time-lapse reservoir property changes and seismic attributes. The method can simultaneously utilize multiple seismic attributes, including attributes derived from prestack seismic, from multiple 4D seismic surveys. It significantly improves the efficiency and reduces the cycle time for quantitative 4D interpretation. We evaluate the method through a study based on synthetic data modeled after a complex North Sea reservoir with long production and injection history. For this reservoir, separation and estimation of the time-lapse pressure and saturation change are the critical objectives. Results show high prediction accuracy for all the reservoir properties including pressure, saturations, and compaction changes for the blind validation test. Estimated maps of all the reservoir property changes match very well with the simulation model in the synthetic study. This work also demonstrates that prestack seismic attributes significantly improved the estimation of 4D pressure and saturation changes.

The Interim Analysis of the Optima (observation of GPI-anchored protein-deficient [PNH-type]) Cells in Japanese Patients with Bone Marrow Failure Syndrome and in Those Suspected of Having PNH) Study

[Background] Paroxysmal nocturnal hemoglobinuria (PNH) is a hematopoietic stem cell disorder derived from an acquired mutation of the phosphatidylinositol glycan class A (PIGA) gene in the hematopoietic stem cells which results in the expansion of glycosylphospatidylinositol-anchored protein (GPI-AP)-deficient (PNH-type) hematopoietic cells. PNH-type blood cells are also observed in patients with bone marrow failure (BMF). PNH is conventionally diagnosed when patients have >1% of GPI-AP-deficient erythrocytes and granulocytes determined by flow cytometry. Analyses with high resolution flow cytometry by several different groups have shown that patients with aplastic anemia (AA) or low-risk types of myelodysplastic syndromes (MDS) have small percentages of PNH-type erythrocytes, granulocytes, and/or other lineages of blood cells and that these patients respond better to immunosuppressive therapies compared with BMF patients lacking PNH-type cells. In order to determine the prevalence and clinical significance of PNH-type cells in BMF patients, we conducted a nationwide multi-center prospective observational investigation, the OPTIMA study.[Methods] From July 2011, Japanese patients with PNH, AA, MDS or BMF of uncertain origin have been prospectively enrolled into the study. Six laboratories in different cities in Japan were assigned as regional analyzing centers and measured the percentages of PNH-type cells in the study population as well as collecting clinical and laboratory data. The high-resolution flow cytometry assessments used a liquid fluorescein-labeled proaerolysin (FLAER) method and a cocktail method with anti-CD55 and anti-CD59 antibodies for the detection of PNH-type granulocytes and erythrocytes, respectively. Periodic blind cross validation tests using a standard blood sample containing 0.01% PNH-type cells and a normal control were conducted to minimize inter-laboratory variations. From analysis of 68 healthy individuals >0.003% of PNH-type granulocytes and >0.005% of PNH-type erythrocytes were considered to be abnormal (Sugimori et al, Blood, 2006).[Results] As of May 2014, flow cytometry data have been collected from 1685 patients and are included in this interim analysis. Of these patients, 65 (4%) were diagnosed with PNH, 523 (31%) with AA, 459 (27%) with MDS, and 638 (38%) with BMF of unknown etiology. Overall, 154 (9%) patients had ≥1% of both PNH-type erythrocytes and granulocytes: 63 (97%) patients with PNH; 57 (11%) with AA; 18 (4%) with MDS; and 16 (3%) with BMF of unknown etiology. In total, 545 (32%) patients had ≥0.005% PNH-type erythrocytes and ≥0.003% PNH-type granulocytes. These consisted of the followings; all 65 (100%) patients with PNH; 264 (51%) with AA; 76 (17%) with MDS; and 140 (22%) with BMF of unknown origin. Lactate dehydrogenase (LDH) levels ≥1.5 × upper limit of normal range were seen in 14/329 (4%) patients with 0.005-1% PNH-type erythrocytes, 23/62 (37%) patients with 1-10% PNH-type erythrocytes, and 69/71 (97%) patients with ≥10% PNH-type erythrocytes. Periodic blind validation tests revealed that inter-laboratory differences in absolute measurements of PNH-type cells were always within 0.02%.[Conclusion] A high-resolution flow cytometry-based method, based on the Kanazawa method, that enables the detection of very low percentages of PNH-type cells was successfully transferred to 6 laboratories across Japan. Our results demonstrated that the proportion of patients identified as having small percentages of PNH-type cells differed depending on diagnosis (PNH, AA, MDS, or unknown BMF) and that elevated LDH levels (>1.5 x upper limits of normal range) were more frequently associated with higher percentages of PNH-type erythrocytes. Our findings suggest that the high resolution method is helpful as a diagnostic tool in BMF syndromes, including AA, MDS, and PNH, and may prove useful in understanding the pathophysiology of these disorders. DisclosuresNoji:Alexion Pharma: Honoraria. Shichishima:Alexion Pharmaceuticals, Inc; and Medical Review Company: Honoraria, Research Funding. Obara:Alexion Pharma: Research Funding. Chiba:Alexion Pharma: Research Funding. Ando:Alexion Pharma: Research Funding. Hayashi:Alexion Pharma: Research Funding. Yonemura:Alexion Pharma: Research Funding. Kawaguchi:Alexion Pharma: Honoraria. Ninomiya:Alexion Pharma: Honoraria, Research Funding. Nishimura:Alexion Pharma: Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau. Kanakura:Alexion Pharma: Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau.

Baseline Assessment Of GPI-Anchored Protein Deficient Blood Cells In Patients With Bone Marrow Failure (The OPTIMA study)

BackgroundParoxysmal nocturnal hemoglobinuria (PNH) is a disease derived from an acquired mutation of the phosphatidylinositol glycan class A (PIGA) gene in the hematopoietic stem cells. In some cases with aplastic anemia (AA) or low-risk types of myelodysplastic syndromes (MDS), it is known that glycosylphosphatidylinositol-anchored protein deficient (PNH-type) cells can be often detected at low frequencies (about 0.01%) through the high-resolution flow cytometry-based methFod. Because these patient groups are reported to have a good reactivity towards immunosuppressive therapies as opposed to the other patient groups lacking PNH-type cells, detection of these cells is potentially useful in determining a treatment plan for the patients with bone marrow failure syndromes. To confirm this preliminary information, a large cohort study is needed. MethodA nationwide multi-center prospective observational study (OPTIMA) was started in July 2011 to determine the prevalence of patients with bone marrow failure syndromes who carried PNH-type cells and to clarify the significance of the presence and quantitative changes of these cells with regard to the clinical features. Each of the six laboratories in different universities was assigned as a regional analyzing center. The percentage of PNH-type cells was measured by the high-resolution flow cytometry-based method, originally established in Kanazawa University. At six individual laboratories, cross validations were conducted to minimize the inter-laboratory variations in the detection sensitivities, cutoff values, etc. The liquid FLAER method (≥0.003%) and cocktail method (≥0.005%) with CD55 and CD59 antibodies were used for the detection of PNH-type granulocytes and erythrocytes, respectively. ResultsQuality of the assay was managed in all the laboratories by periodic blind validation tests using standard blood samples containing 0.01% PNH-type cells. Until July 2013, 1214 cases were examined; 461 (38%) were positive for PNH-type cells and 141 (11.6%) had ≥1% PNH-type cells. Out of 1214, 783 patients were diagnosed to have AA (n=386), MDS (n=341), and PNH (n=56) based on the case report forms. PNH-type cells were detected in 56.2%, 19.1% and 100% of patients with AA, MDS and PNH, respectively. In a half of patients having ≥1% PNH-type cells, lactate dehydrogenase levels exceeded the ≥1.5×upper limits of normal. ConclusionOur study has successfully established the high-resolution flow cytometry-based method that enables the detection of minimal PNH-type cells (below 0.01%). Also, by implementing a uniform protocol to six individual laboratories across the country, a system has been established for the patients to undergo the detection test with equal accuracy in all of these laboratories. Further accumulation of case studies and prolonged observations are required to determine the clinical significance of the minimal PNH-type cells, especially in terms of its relation to response to immunosuppressive therapy. Disclosures:Obara:Alexion Pharmaceuticals: Honoraria. Chiba:Alexion Pharmaceuticals, In: Research Funding. Sugimori:Alexion Pharma: Honoraria. Noji:Alexion Pharmaceuticals: Honoraria. Yonemura:Alexion Pharma: Research Funding. Ando:Alexion Pharma: Research Funding. Kawaguchi:Alexion Pharmaceuticals: Honoraria. Shichishima:Alexion Pharmaceuticals, In: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Ninomiya:Alexion Pharma: Honoraria. Nishimura:Alexion Pharma: Research Funding, Speakers Bureau. Kanakura:Alexion Pharmaceuticals: Research Funding, Speakers Bureau. Nakao:Alexion Pharmaceuticals, In: Research Funding.

Prediction of the Free Energy of Hydration of a Challenging Set of Pesticide-Like Compounds

In a blind validation test the COSMO-RS method, a combination of the quantum chemical dielectric continuum solvation model COSMO with a statistical thermodynamics treatment for more realistic solvation (RS) simulations, has been used for the direct prediction of transfer free energies of 55 demanding pesticide-like compounds. Comparison with experimental data yields an rms deviation of approximately 2 kcal/mol, which is in the order of the estimated inaccuracy of the experimental data. A detailed comparison reveals experimental and calculation pitfalls on conformational flexible, multifunctional, polar compounds.

Hierarchical high-throughput SNP genotyping of the human Y chromosome using MALDI-TOF mass spectrometry.

We have established the use of a primer extension/mass spectrometry method (the PinPoint assay) for high-throughput SNP genotyping of the human Y chromosome. 118 markers were used to define 116 haplogroups and typing was organised in a hierarchical fashion. Twenty multiplex PCR/primer extension reactions were set up and each sample could be assigned to a haplogroup with only two to five of these multiplex analyses. A single aliquot of one enzyme was found to be sufficient for both PCR and primer extension. We observed 100% accuracy in blind validation tests. The technique thus provides a reliable, cost-effective and automated method for Y genotyping, and the advantages of using a hierarchical strategy can be applied to any DNA segment lacking recombination.

Water Leak Testing of Polyurethane Female Condoms

Abstract This paper describes an apparatus and a technique for water leak testing of polyurethane female condoms. This test detects holes as effectively as other official FDA methods used to test barrier products such as latex male condoms and medical gloves. This rapid test simulates actual use conditions as much as possible without causing plastic deformation of the polyurethane material. Blind validation tests showed that the method detects a high percentage of holes 20 μm and larger over the entire surface of the condoms. Holes as small as 10 μm were detected with lower efficiency. Hole detection rate was highest in the bottom one third of the condom where the water pressure was greatest. The condom lubricant was shown to act as a surfactant when added to water.