Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations

Supervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality control. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide an efficient modeling and supervision framework. A new type of MPLS modeling technique that is especially suitable for online real-time process monitoring and the multivariate monitoring charts are presented. This online process monitoring technique is also extended to include predictions of end-of-batch quality measurements during the progress of a batch run. Process monitoring, quality estimation and fault diagnosis activities are automated and supervised by embedding them into a real-time knowledge-based system (RTKBS). Interpretation of multivariate charts is also automated through a generic rule-base for efficient alarm handling. The integrated RTKBS and the implementation of MPLS-based process monitoring and quality control are illustrated using a fed-batch penicillin production benchmark process simulator.     

A parallel algorithm for robust fault detection in semiconductor manufacturing processes

The semiconductor manufacturing consists of a number of processes, and even a small fault occurring at any point can damage the product quality. The fast and accurate detection of such faults is essential to maintain high manufacturing yields. In this paper, we propose a parallel algorithm for fault detection in semiconductor manufacturing processes. The algorithm is a modification of the discord detection algorithm called HOT SAX, which adopted the SAX representation of time-series for efficient storage and computation. We first propose a sequential algorithm and then extend it to a parallel version. We evaluate our algorithm through experiments using the data obtained from a real-world semiconductor plasma etching process. As a result, our fault detection algorithm achieved 100 % accuracy without any false positive or false negative.     

Discovery of inhibitors of the pentein superfamily protein dimethylarginine dimethylaminohydrolase (DDAH), by virtual screening and hit analysis

An efficient process for the discovery of inhibitors of DDAH enzymes, without the requirement for high throughput screening, is described. Physicochemical filtering of a 308,000-compound library according to drug likeness followed by reciprocal nearest neighbour selection produced a representative subset of 35,000 compounds. Virtual screening on a dual processor PC using FlexX, followed by biological screening, identified two hit series. Similarity searches of commercial databases and chemical re-synthesis of pure compounds resulted in SR445 as an inhibitor of Pseudomonas aeruginosa DDAH at 2 microM.     

Online sequential extreme studentized deviate tests for anomaly detection in streaming data with varying patterns

In the new era of big data, numerous information and technology systems can store huge amounts of streaming data in real time, for example, in server-access logs on web application servers. The importance of anomaly detection in voluminous quantities of streaming data from such systems is rapidly increasing. One of the biggest challenges in the detection task is to carry out real-time contextual anomaly detection in streaming data with varying patterns that are visually detectable but unsuitable for a parametric model. Most anomaly detection algorithms have weaknesses in dealing with streaming time-series data containing such patterns. In this paper, we propose a novel method for online contextual anomaly detection in streaming time-series data using generalized extreme studentized deviates (GESD) tests. The GESD test is relatively accurate and efficient because it performs statistical hypothesis testing but it is unable to handle streaming time-series data. Thus, focusing on streaming time-series data, we propose an online version of the test capable of detecting outliers under varying patterns. We perform extensive experiments with simulated data, syntactic data, and real online traffic data from Yahoo Webscope, showing a clear advantage of the proposed method, particularly for analyzing streaming data with varying patterns.

     

SRAdb: query and use public next-generation sequencing data from within R

Background

The Sequence Read Archive (SRA) is the largest public repository of sequencing data from the next generation of sequencing platforms including Illumina (Genome Analyzer, HiSeq, MiSeq, .etc), Roche 454 GS System, Applied Biosystems SOLiD System, Helicos Heliscope, PacBio RS, and others.

Results

SRAdb is an attempt to make queries of the metadata associated with SRA submission, study, sample, experiment and run more robust and precise, and make access to sequencing data in the SRA easier. We have parsed all the SRA metadata into a SQLite database that is routinely updated and can be easily distributed. The SRAdb R/Bioconductor package then utilizes this SQLite database for querying and accessing metadata. Full text search functionality makes querying metadata very flexible and powerful. Fastq files associated with query results can be downloaded easily for local analysis. The package also includes an interface from R to a popular genome browser, the Integrated Genomics Viewer.

Conclusions

SRAdb Bioconductor package provides a convenient and integrated framework to query and access SRA metadata quickly and powerfully from within R.     

Loop-mediated isothermal amplification (LAMP) method for rapid detection of Trypanosoma brucei rhodesiense

Loop-mediated isothermal amplification (LAMP) of DNA is a novel technique that rapidly amplifies target DNA under isothermal conditions. In the present study, a LAMP test was designed from the serum resistance-associated (SRA) gene of Trypanosoma brucei rhodesiense, the cause of the acute form of African sleeping sickness, and used to detect parasite DNA from processed and heat-treated infected blood samples. The SRA gene is specific to T. b. rhodesiense and has been shown to confer resistance to lysis by normal human serum. The assay was performed at 62 degrees C for 1 h, using six primers that recognised eight targets. The template was varying concentrations of trypanosome DNA and supernatant from heat-treated infected blood samples. The resulting amplicons were detected using SYTO-9 fluorescence dye in a real-time thermocycler, visual observation after the addition of SYBR Green I, and gel electrophoresis. DNA amplification was detected within 35 min. The SRA LAMP test had an unequivocal detection limit of one pg of purified DNA (equivalent to 10 trypanosomes/ml) and 0.1 pg (1 trypanosome/ml) using heat-treated buffy coat, while the detection limit for conventional SRA PCR was approximately 1,000 trypanosomes/ml. The expected LAMP amplicon was confirmed through restriction enzyme RsaI digestion, identical melt curves, and sequence analysis. The reproducibility of the SRA LAMP assay using water bath and heat-processed template, and the ease in results readout show great potential for the diagnosis of T. b. rhodesiense in endemic regions.     

Knapsack - TOPSIS Technique for Vertical Handover in Heterogeneous Wireless Network

In a heterogeneous wireless network, handover techniques are designed to facilitate anywhere/anytime service continuity for mobile users. Consistent best-possible access to a network with widely varying network characteristics requires seamless mobility management techniques. Hence, the vertical handover process imposes important technical challenges. Handover decisions are triggered for continuous connectivity of mobile terminals. However, bad network selection and overload conditions in the chosen network can cause fallout in the form of handover failure. In order to maintain the required Quality of Service during the handover process, decision algorithms should incorporate intelligent techniques. In this paper, a new and efficient vertical handover mechanism is implemented using a dynamic programming method from the operation research discipline. This dynamic programming approach, which is integrated with the Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) method, provides the mobile user with the best handover decisions. Moreover, in this proposed handover algorithm a deterministic approach which divides the network into zones is incorporated into the network server in order to derive an optimal solution. The study revealed that this method is found to achieve better performance and QoS support to users and greatly reduce the handover failures when compared to the traditional TOPSIS method. The decision arrived at the zone gateway using this operational research analytical method (known as the dynamic programming knapsack approach together with Technique to Order Preference by Similarity to Ideal Solution) yields remarkably better results in terms of the network performance measures such as throughput and delay.     

'Real-time' PCR-based detection of Coxiella burnetii using conventional techniques

The diagnosis of Q fever (Coxiella burnetii infection) relies primarily on the serological detection of specific antibodies. Recently, PCR-based methods have been introduced in diagnostic laboratories. Unfortunately, the fastest and most reliable 'real-time' detection method, which employs the 'online' detection of target nucleotide sequences while the amplification process is still in progress, requires expensive devices and consumables. In this study, we present a simple method that combines the simplicity of conventional PCR with new technical and methodical enhancements, resulting in a fast, specific and easy method for the molecular detection of C. burnetii. A collection of C. burnetii reference strains was tested with the modified conventional gel-based PCR approach applying a particluar PCR buffer (QIAGEN(?) Fast Cycling PCR kit) and using a closed ready-to-use gel-cassette-system (FlashGel(?)) for the visualization of specific PCR products. The modified conventional PCR method reached nearly the speed of the LightCycler(?) HybProbe real-time PCR assay (120 vs. 90 min) and showed equal sensitivity and specificity. The general cost per PCR run was 25% less than that for the LightCycler method. These improvements make this method suitable for small laboratories with limited resources and for deployable PCR diagnostics in field laboratories.     

Monitoring of a sequencing batch reactor using adaptive multiblock principal component analysis

Multiway principal component analysis (MPCA) for the analysis and monitoring of batch processes has recently been proposed. Although MPCA has found wide applications in batch process monitoring, it assumes that future batches behave in the same way as those used for model identification. In this study, a new monitoring algorithm, adaptive multiblock MPCA, is developed. The method overcomes the problem of changing process conditions by updating the covariance structure recursively. A historical set of operational data of a multiphase batch process was divided into local blocks in such a way that the variables from one phase of a batch run could be blocked in the corresponding blocks. This approach has significant benefits because the latent variable structure can change for each phase during the batch operation. The adaptive multiblock model also allows for easier fault detection and isolation by looking at the relationship between blocks and at smaller meaningful block models, and it therefore helps in the diagnosis of the disturbance. The proposed adaptive multiblock monitoring method is successfully applied to a sequencing batch reactor for biological wastewater treatment.     

Quantitation of viral DNA by real-time PCR applying duplex amplification, internal standardization, and two-color fluorescence detection

A real-time PCR method was developed to quantitate viral DNA that includes duplex amplification, internal standardization, and two-color fluorescence detection without the need to generate an external standardization curve. Applied to human parvovirus B19 DNA, the linear range was from 10(2) to at least 5 x 10(6) copies per ml of sample. The coefficient of variation was 0.29 using a run control of 2,876 copies per ml. The method reduces the risk of false-negative results, yields high precision, and is applicable for other DNA targets.     

多孔硅Bragg反射镜适配子生物传感器检测心肌肌钙蛋白I

通过脉冲腐蚀法制备多孔硅Bragg反射镜,将心肌肌钙蛋白I（cTnI）适配子共价固定到多孔硅Bragg反射镜的孔洞中,发现适配子能与cTnI分子特异性结合。定量分析不同浓度的cTnI与适配子结合后多孔硅Bragg反射镜的反射谱峰位的红移情况。结果表明：基于多孔硅Bragg反射镜适配子生物传感器的光学检测具有良好的特异性,且具有免标记及检测时间短等优异性能。传感器的线性检测范围0．05-4nmol／L,最低检测限为0．05nmol／L。     

Computational Effective Fault Detection by Means of Signature Functions

The paper presents a computationally effective method for fault detection. A system’s responses are measured under healthy and ill conditions. These signals are used to calculate so-called signature functions that create a signal space. The current system’s response is projected into this space. The signal location in this space easily allows to determine the fault. No classifier such as a neural network, hidden Markov models, etc. is required. The advantage of this proposed method is its efficiency, as computing projections amount to calculating dot products. Therefore, this method is suitable for real-time embedded systems due to its simplicity and undemanding processing capabilities which permit the use of low-cost hardware and allow rapid implementation. The approach performs well for systems that can be considered linear and stationary. The communication presents an application, whereby an industrial process of moulding is supervised. The machine is composed of forms (dies) whose alignment must be precisely set and maintained during the work. Typically, the process is stopped periodically to manually control the alignment. The applied algorithm allows on-line monitoring of the device by analysing the acceleration signal from a sensor mounted on a die. This enables to detect failures at an early stage thus prolonging the machine’s life.     

Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound action potentials in neural regeneration studies.     

Run-to-run fed-batch optimization for protein production using recombinant Escherichia coli

A two-phase design approach is introduced to determine the optimal feed rate, fed glucose concentration and fermentation time to maximize protein productivity using recombinant Escherichia coli BL21 (pBAW2) strain. The first phase is applied to determine a primary S-system kinetic model using batch time-series data. Two runs were carried out in the second phase to achieve the maximum protein productivity for the fed-batch fermentation process. The computational results using the S-system kinetic model obtained from the second run are in better agreement with the experiments than those using the kinetic model obtained from batch time-series data. For cross-validation, two extra fed-batch experiments with different feed strategies were carried out for comparison with the optimal fed-batch result. From the experimental results, this approach could improve productivity by at least 3%.     

An efficient quantitation method of next-generation sequencing libraries by using MiSeq sequencer

Library quantitation is a critical step to obtain high data output in Illumina HiSeq sequencers. Here, we introduce a library quantitation method that uses the Illumina MiSeq sequencer designated as quantitative MiSeq (qMiSeq). In this procedure, 96 dual-index libraries, including control samples, are denatured, pooled in equal volume, and sequenced by MiSeq. We found that relative concentration of each library can be determined based on the observed index ratio and can be used to determine HiSeq run condition for each library. Thus, qMiSeq provides an efficient way to quantitate a large number of libraries at a time.     

MRCQuant- an accurate LC-MS relative isotopic quantification algorithm on TOF instruments

Background  

Relative isotope abundance quantification, which can be used for peptide identification and differential peptide quantification, plays an important role in liquid chromatography-mass spectrometry (LC-MS)-based proteomics. However, several major issues exist in the relative isotopic quantification of peptides on time-of-flight (TOF) instruments: LC peak boundary detection, thermal noise suppression, interference removal and mass drift correction. We propose to use the Maximum Ratio Combining (MRC) method to extract MS signal templates for interference detection/removal and LC peak boundary detection. In our method, MRCQuant, MS templates are extracted directly from experimental values, and the mass drift in each LC-MS run is automatically captured and compensated. We compared the quantification accuracy of MRCQuant to that of another representative LC-MS quantification algorithm (msInspect) using datasets downloaded from a public data repository.     

Trait‐abundance relation in response to nutrient addition in a Tibetan alpine meadow: The importance of species trade‐off in resource conservation and acquisition

In competition‐dominated communities, traits promoting resource conservation and competitive ability are expected to have an important influence on species relative abundance (SRA). Yet, few studies have tested the trait‐abundance relations in the line of species trade‐off in resource conservation versus acquisition, indicating by multiple traits coordination. We measured SRA and key functional traits involving leaf economic spectrum (SLA, specific leaf area; LDMC, leaf dry matter content; LCC, leaf carbon concentration; LNC, leaf nitrogen concentration; LPC, leaf phosphorus concentration; Hs, mature height) for ten common species in all plots subjected to addition of nitrogen fertilizer (N), phosphorus fertilizer (P), or both of them (NP) in a Tibetan alpine meadow. We test whether SRA is positively related with traits promoting plant resource conservation, while negatively correlated with traits promoting plant growth and resource acquisition. We found that species were primarily differentiated along a trade‐off axis involving traits promoting nutrient acquisition and fast growth (e.g., LPC and SLA) versus traits promoting resource conservation and competition ability (e.g., large LDMC). We further found that SRA was positively correlated with plant height, LDMC, and LCC, but negatively associated with SLA and leaf nutrient concentration irrespective of fertilization. A stronger positive height‐SRA was found in NP‐fertilized plots than in other plots, while negative correlations between SRA and SLA and LPC were found in N or P fertilized plots. The results indicate that species trade‐off in nutrient acquisition and resource conservation was a key driver of SRA in competition‐dominated communities following fertilization, with the linkage between SRA and traits depending on plant competition for specific soil nutrient and/or light availability. The results highlight the importance of competitive exclusion in plant community assembly following fertilization and suggest that abundant species in local communities become dominated at expense of growth while infrequent species hold an advantage in fast growth and dispersals to neighbor meta‐communities.