Immobilised activated sludge based biosensor for biochemical oxygen demand measurement

A biochemical oxygen demand (BOD) sensor, based on an immobilised mixed culture of microorganisms in combination with a dissolved oxygen electrode, has been developed for the purpose of on-line monitoring of the biological treatment process for waste and wastewater. The sensor was designed for easy replacement of the biomembrane, thereby making it suitable for short-term use. The drawbacks of activated sludge based sensor, such as short sensor lifetime, were thereby circumvented. The sensor BOD measurements were carried out in the kinetic mode using a flow injection system, resulting in 25 s for one measurement followed by 4–8 min recovery time. Based on the results of normalised sensor responses, the OECD synthetic wastewater was considered to be a more suitable calibration solution in comparison with the GGA solution. Good agreement was achieved between the results of the sensor BOD measurement and those obtained from BOD₅ analysis of a wastewater sample from a food-processing factory. Reproducibility of responses using one sensor was below ±5.6% standard deviation. Reproducibility of responses using different sensors was within acceptable bias limits, viz. ±15% standard deviation.     

培养基除菌过滤在百日咳菌苗生产中的应用

经一系列试验证实百日咳菌大罐培养浓度的下降与培养基中不耐热营养因子不足有关,将培养基的高压灭菌方式改为除菌过滤,保留热不稳定营养因子,可以提高百日咳菌大罐培养浓度;优化酸沉淀条件后,提高了菌苗回收率,从而节省了大量培养基,缩短了生产时间,获得了良好的经济效益。     

动态心电图在小儿心律失常与心率变异性诊断中的意义

目的：研究动态心电图（DCG）诊断小儿心律失常及心率变异性（HVR）的临床价值。方法：560 例患者均进行常规心电图和动 态心电图的检查,由两组专业人员分别对心电图（ECG）和动态心电图（DCG）的检查结果进行（评价）,比较两种检查手段的不同 类型的心律失常的诊出率;评价不同类型心律失常的HVR。结果：ECG对各型心律失常的总诊出率为25.00%,对不同类型心率失 常的诊出率分别为5.71%、1.43%、9.29%、6.43%和2.14%;DCG 总诊出率为62.85%,对不同类型心率失常的诊出率分别为 16.43%、6.43%、17.86%、14.29%和7.86%,二者具有统计学差异（P＜0.05）。不同类型的心律失常的HVR不同,其中室性心动过速 和室性期前收缩的各项指标均明显低于其他类型（P＜0.05）。结论：DCG对不同心律失常的诊出率明显高于ECG,并能有效反应 不同类型心率失常的HVR,在小儿心律失常的诊断中具有一定的临床价值。     

Stability measurements of antibodies stored on paper

Reagent storage has been a long-standing challenge for diagnostics, especially those designed for low-resource settings and point-of-care applications. In general, the stability of a reagent relies on careful temperature control, often by refrigeration, which is costly and often unavailable in these remote settings. Poor reagent integrity can negatively affect the reproducibility and reliability of an assay. Given the recent interest in paper-based devices designed for quantitative analysis in point-of-care settings, a better understanding of reagent stability on filter paper is critical for proper device use and its longevity. In this article, we present an independent method to examine the stability of reconstituted antibodies that were stored on filter paper using flow cytometry. We validated the method by measuring the activity as measured by the mean fluorescence intensity (MFI) of antibodies stored with known stabilizers. Furthermore, we demonstrated the potential of our method to screen the influence of other paper treatments and storage processes on antibody stability, which may be applicable to the storage of reagents on paper in general.     

Extension of dynamic range of sensitive nanoparticle-based immunoassays

Nanoparticles have successfully been employed in immunometric assays that require high sensitivity. Certain analytes, however, require dynamic ranges (DRs) around a predetermined cut-off value. Here, we have studied the effects that antibody orientation and addition of free solid-phase and detection antibodies have on assay sensitivity and DR in traditional sandwich-type immunoassays. D-dimer and cardiac troponin I (cTnI), both routinely used in critical care testing, were applied as model analytes. The assays were performed in microtitration wells with preimmobilized solid-phase antibody. Inherently fluorescent nanoparticles coated with second antibody were used to detect the analyte. The selection of antibody orientation and addition of free solid-phase or detection antibody, with nanoparticles and calibrator, desensitized the assays and extended the DR. With D-dimer the upper limit of the DR was improved from 50 to 10,000 ng/ml, and with cTnI from 25 to 1000 ng/ml. Regression analysis with the Stago STA Liatest D-dimer assay yielded a slope (95% confidence interval) of 0.09 (0.07–0.11) and a y-intercept of −7.79 (−17.87–2.29) ng/L (n = 65, r = 0.906). Thus it is concluded that Europium(III)-chelate-doped nanoparticles can also be employed in immunoassays that require wide DRs around a certain cut-off limit.     

Robust and stable feature selection by integrating ranking methods and wrapper technique in genetic data classification

High dimensional data increase the dimension of space and consequently the computational complexity and result in lower generalization. From these types of classification problems microarray data classification can be mentioned. Microarrays contain genetic and biological data which can be used to diagnose diseases including various types of cancers and tumors. Having intractable dimensions, dimension reduction process is necessary on these data. The main goal of this paper is to provide a method for dimension reduction and classification of genetic data sets. The proposed approach includes different stages. In the first stage, several feature ranking methods are fused for enhancing the robustness and stability of feature selection process. Wrapper method is combined with the proposed hybrid ranking method to embed the interaction between genes. Afterwards, the classification process is applied using support vector machine. Before feeding the data to the SVM classifier the problem of imbalance classes of data in the training phase should be overcame. The experimental results of the proposed approach on five microarray databases show that the robustness metric of the feature selection process is in the interval of [0.70, 0.88]. Also the classification accuracy is in the range of [91%, 96%].     

Modelling the optimal timing in metabolic pathway activation—Use of Pontryagin's Maximum Principle and role of the Golden section

The time course of enzyme concentrations in metabolic pathways can be predicted on the basis of the optimality criterion of minimizing the time period in which an essential product is generated. This criterion is in line with the widely accepted view that high fitness requires high pathway flux. Here, based on Pontryagin's Maximum Principle, a method is developed to solve the corresponding constrained optimal control problem in an almost exclusively analytical way and, thus, to calculate optimal enzyme profiles, when linear, irreversible rate laws are assumed. Three different problem formulations are considered and the corresponding optimization results are derived. Besides the minimization of transition time, we consider an operation time in which 90% of the substrate has been converted into product. In that case, only the enzyme at the lower end of the pathway rather than all enzymes are active in the last phase. In all cases, biphasic or multiphasic time courses are obtained. The biological meaning of the results in terms of a consecutive just-in-time expression of metabolic genes is discussed. For the special case of two-enzyme systems, the role of the Golden section in the solution is outlined.     

A label-free nanoparticle aggregation assay for protein complex/aggregate detection and study

The detection, analysis, and understanding of protein complexes/aggregates and their formation process are extremely important for biomolecular research, diagnosis, and biopharmaceutical development. Unfortunately, techniques that can be used conveniently for protein complex/aggregate detection and analysis are very limited. Using gold nanoparticle immunoprobes coupled with dynamic light scattering (DLS), we developed a label-free nanoparticle aggregation immunoassay (NanoDLSay) for protein aggregate detection and study. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), a protein target used routinely in Western blot as a loading control, is demonstrated here as an example. Through this study, we discovered that GAPDH has a strong tendency to form large aggregates in certain buffer solutions at a concentration range of 10-25 μg/ml. The strong light scattering property of gold nanoparticles immunoprobes greatly enhanced the sensitivity of the dynamic light scattering for protein complex/aggregate detection. In contrast to fluorescence techniques for protein complex and aggregation study, the protein targets do not need to be labeled with fluorescent probe molecules in NanoDLSay. NanoDLSay is a very convenient and sensitive tool for protein complex/aggregate detection and study.     

Regret‐Regression for Optimal Dynamic Treatment Regimes

Summary We consider optimal dynamic treatment regime determination in practice. Model building, checking, and comparison have had little or no attention so far in this literature. Motivated by an application on optimal dosage of anticoagulants, we propose a modeling and estimation strategy that incorporates the regret functions of Murphy (2003, Journal of the Royal Statistical Society, Series B 65, 331–366) into a regression model for observed responses. Estimation is quick and diagnostics are available, meaning a variety of candidate models can be compared. The method is illustrated using simulation and the anticoagulation application.