A novel (to the best of our knowledge) liquid level sensor based on multimode interference (MMI) effects is proposed and demonstrated. By using a multimode fiber (MMF) without cladding, known as no-core fiber, liquids around the MMF modify the self-imaging properties of the MMI device and the liquid level can be detected. We show that the sensor exhibits a highly linear response with the sensing range and multiplexed operations easily controlled by just modifying the length of the no-core fiber. At the same time, we can measure the refractive index of the liquid based on the maximum peak wavelength shift. We can also use the sensor for continuous and discrete liquid level sensing applications, thus providing a liquid level sensor that is inexpensive with a very simple fabrication process.

/pdf/fiber-optic-sensor-for-liquid-level-measurement-1us2xcchd4.pdf

Fiber-optic sensor for liquid level measurement.

Acoustic-wave-based sensors are commonly known as mass-sensitive devices. However, acoustic chemical and biochemical sensors also face so-called non-gravimetric effects, especially if they work in a liquid environment. The one-dimensional transmission-line model (TLM) is a powerful tool, which considers the influence of geometric and material properties on the sensor transduction mechanism, most importantly the influence of viscoelastic phenomena. This paper demonstrates the concept of modelling acoustic microsensors on quartz crystal resonators. Particular attention is paid to special cases which allow for simplifications or specific solutions of the TLM, like the acoustic load concept (ALC), the BVD model or the Sauerbrey equation. Deviations from the one-dimensional assumption of the TLM are suspected to significantly contribute to the acoustic sensor response in biosystems. We therefore introduce a generalization of the ALC to get access to two- or three-dimensional effects, which are up to now not considered in the TLM. As examples, signatures of interfacial phenomena or non-uniform films are discussed.

http://iopscience.iop.org/article/10.1088/0957-0233/14/11/002/pdf

Transduction mechanism of acoustic-wave based chemical and biochemical sensors

This paper presents an easy-to-design interface circuit to measure very small-percentage capacitance variations in capacitive sensors, especially suitable for industrial measurements. A computer-controlled 24-bit A/D converter is employed to obtain a higher resolution. This interface circuit can be used with various types of capacitive sensors. The most interesting thing is, that the measurement results through this interface circuit are independent of the initial capacitance of the sensor. In addition, the double differential operating principle used here minimizes the error caused by coupling and stray capacitance of sensor probes. The operating principle of the designed interface circuit, the major assumptions made, test data, and possible future developments are discussed.

A simple interface circuit to measure very small capacitance changes in capacitive sensors

The conventional capacitance-type liquid level sensor consists of an insulated solid metallic rod electrode immersed in the liquid contained in a metallic storage tank, or two such identical electrodes in a nonmetallic storage tank. Such metallic rods may suffer from the self-inductance effect which varies nonlinearly with the level. In this paper, we present a modified capacitance-type level sensor in which effect of self-inductance of the metallic rod has been eliminated. The theoretical equations describing the operation of the sensor are derived. The sensor is designed and tested experimentally and is found to follow the theoretical equations. The experimental results are also presented. A very good linearity of the sensor is observed.

Study of a Modified Capacitance-Type Level Transducer for Any Type of Liquid

A sensor suitable for online monitoring of viscosity and density of glycerol–water mixtures is presented. The device is based on Lorentz force excitation and features an integrated piezoresistive readout. The core sensing element is a rectangular vibrating plate suspended by four beam springs. Two of the plate-carrying springs comprise piezoresistors. With two additional resistors on the silicon rim they form a half Wheatstone-bridge. Through the conductive layer of the beam springs a sinusoidal excitation current is driven. In the field of a permanent magnet, the Lorentz force excites plate vibrations resulting in a bridge unbalance. We recorded both the frequency response of the amplitude and the phase of the bridge output. By evaluating the properties of the resonant system, it is possible to extract the glycerol percentage and, hence, the viscosity and the mass density of the mixtures.

/pdf/sensing-viscosity-and-density-of-glycerol-water-mixtures-57f3nf0cep.pdf

Sensing viscosity and density of glycerol–water mixtures utilizing a suspended plate MEMS resonator

A new capacitive precision liquid-level gauge has been developed. The sensor consists of a low-cost planar electrode structure, a capacitance-controlled oscillator and a microcontroller. The device is able to measure absolute levels of conducting and nonconducting liquids with a 1 mm uncertainty over a 4 m range. The system has a high resolution of 0.1 mm at short measuring times of only 0.2 s. Slow level movements of 0.02 mm/h can be detected within 18 min.

/pdf/a-planar-capacitive-precision-gauge-for-liquid-level-and-1xibegbj3k.pdf

A planar capacitive precision gauge for liquid-level and leakage detection

Cytochrome P450 3A (CYP3A) subfamily enzymes are involved in the metabolism of 40% of drugs in clinical use. Twin studies have indicated that 66% of the variability in CYP3A4 activity is hereditary. Yet, the complexity of the CYP3A locus and the lack of distinct drug metabolizer phenotypes has limited the identification and clinical application of CYP3A genetic variants compared to other Cytochrome P450 enzymes. In recent years evidence has emerged indicating that a substantial part of the missing heritability is caused by low frequency genetic variation. In this review, we outline the current pharmacogenomics knowledge of CYP3A activity and discuss potential future directions to improve our genetic knowledge and ability to explain CYP3A variability.

/pdf/why-we-need-to-take-a-closer-look-at-genetic-contributions-1bygdpsj.pdf

Why We Need to Take a Closer Look at Genetic Contributions to CYP3A Activity

Abstract This pilot study is aimed at implementing an approach for comprehensive clinical pharmacogenomics (PGx) profiling. Fifty patients with cardiovascular diseases and 50 healthy individuals underwent whole-exome sequencing. Data on 1800 PGx genes were extracted and analyzed through deep filtration separately. Theoretical drug induced phenoconversion was assessed for the patients, using sequence2script . In total, 4539 rare variants (including 115 damaging non-synonymous) were identified. Four publicly available PGx bioinformatics algorithms to assign PGx haplotypes were applied to nine selected very important pharmacogenes (VIP) and revealed a 45–70% concordance rate. To ensure availability of the results at point-of-care, actionable variants were stored in a web-hosted database and PGx-cards were developed for quick access and handed to the study subjects. While a comprehensive clinical PGx profile could be successfully extracted from WES data, available tools to interpret these data demonstrated inconsistencies that complicate clinical application. 

/pdf/development-of-an-extensive-workflow-for-comprehensive-mgapiakv.pdf

Development of an extensive workflow for comprehensive clinical pharmacogenomic profiling: lessons from a pilot study on 100 whole exome sequencing data

In recent years, the use of artificial intelligence (AI) in health care has risen steadily, including a wide range of applications in the field of pharmacology. AI is now used throughout the entire continuum of pharmacology research and clinical practice and from early drug discovery to real‐world datamining. The types of AI models used range from unsupervised clustering of drugs or patients aimed at identifying potential drug compounds or suitable patient populations, to supervised machine learning approaches to improve therapeutic drug monitoring. Additionally, natural language processing is increasingly used to mine electronic health records to obtain real‐world data. In this mini‐review, we discuss the basics of AI followed by an outline of its application in pharmacology research and clinical practice.

/pdf/artificial-intelligence-in-pharmacology-research-and-1hk5v18d.pdf

Artificial intelligence in pharmacology research and practice

Background: Inter-individual differences in drug response based on genetic variations can lead to drug toxicity and treatment inefficacy. A large part of this variability is caused by genetic variants in pharmacogenes. Unfortunately, the Single Nucleotide Variant arrays currently used in clinical pharmacogenomic (PGx) testing are unable to detect all genetic variability in these genes. Long-read sequencing, on the other hand, has been shown to be able to resolve complex (pharmaco) genes. In this study we aimed to assess the value of long-read sequencing for research and clinical PGx focusing on the important and highly polymorphic CYP2C19 gene. Methods and Results: With a capture-based long-read sequencing panel we were able to characterize the entire region and assign variants to their allele of origin (phasing), resulting in the identification of 813 unique variants in 37 samples. To assess the clinical utility of this data we have compared the performance of three different *-allele tools (Aldy, PharmCat and PharmaKU) which are specifically designed to assign haplotypes to pharmacogenes based on all input variants. Conclusion: We conclude that long-read sequencing can improve our ability to characterize the CYP2C19 locus, help to identify novel haplotypes and that *-allele tools are a useful asset in phenotype prediction. Ultimately, this approach could help to better predict an individual’s drug response and improve therapy outcomes. However, the added value in clinical PGx might currently be limited.

/pdf/from-gene-to-dose-long-read-sequencing-and-allele-tools-to-23zrj3df.pdf

M. van der Lee

Papers

A planar capacitive precision gauge for liquid-level and leakage detection

Why We Need to Take a Closer Look at Genetic Contributions to CYP3A Activity

Development of an extensive workflow for comprehensive clinical pharmacogenomic profiling: lessons from a pilot study on 100 whole exome sequencing data

Artificial intelligence in pharmacology research and practice

From gene to dose: Long-read sequencing and *-allele tools to refine phenotype predictions of CYP2C19