Acoustic detection of a mutation-specific Ligase Chain Reaction based on liposome amplification.

Single nucleotide variants (SNVs) play a crucial role in understanding genetic diseases, cancer development, and personalized medicine. However, existing ligase-based amplification and detection techniques, such as Rolling Circle Amplification and Ligase Detection Reaction, suffer from low efficiency and difficulties in product detection. To address these limitations, we propose a novel approach that combines Ligase Chain Reaction (LCR) with acoustic detection using highly dissipative liposomes. In our study, we are using LCR combined with biotin- and cholesterol-tagged primers to produce amplicons also modified at each end with a biotin and cholesterol molecule. We then apply the LCR mix without any purification directly on a neutravidin modified QCM device Au-surface, where the produced amplicons can bind specifically through the biotin end. To improve sensitivity, we finally introduce liposomes as signal enhancers. For demonstration, we used the detection of the BRAF V600E point mutation versus the wild-type allele, achieving an impressive detection limit of 220 aM of the mutant target in the presence of the same amount of the wild type. Finally, we combined the assay with a microfluidic fluidized bed DNA extraction technology, offering the potential for semi-automated detection of SNVs in patients' crude samples. Overall, our LCR/acoustic method outperforms other LCR-based approaches and surface ligation biosensing techniques in terms of detection efficiency and time. It effectively overcomes challenges related to DNA detection, making it applicable in diverse fields, including genetic disease and pathogen detection.

Uncertainty quantification of time-average quantities of chaotic systems using sensitivity-enhanced polynomial chaos expansion.

We consider the effect of multiple stochastic parameters on the time-average quantities of chaotic systems. We employ the recently proposed sensitivity-enhanced generalized polynomial chaos expansion, se-gPC, to quantify efficiently this effect. se-gPC is an extension of gPC expansion, enriched with the sensitivity of the time-averaged quantities with respect to the stochastic variables. To compute these sensitivities, the adjoint of the shadowing operator is derived in the frequency domain. Coupling the adjoint operator with gPC provides an efficient uncertainty quantification algorithm, which, in its simplest form, has computational cost that is independent of the number of random variables. The method is applied to the Kuramoto-Sivashinsky equation and is found to produce results that match very well with Monte Carlo simulations. The efficiency of the proposed method significantly outperforms sparse-grid approaches, such as Smolyak quadrature. These properties make the method suitable for application to other dynamical systems with many stochastic parameters.

Acoustic Array Biochip Combined with Allele-Specific PCR for Multiple Cancer Mutation Analysis in Tissue and Liquid Biopsy.

Regular screening of point mutations is of importance to cancer management and treatment selection. Although techniques like next-generation sequencing and digital polymerase chain reaction (PCR) are available, these are lacking in speed, simplicity, and cost-effectiveness. The development of alternative methods that can detect the extremely low concentrations of the target mutation in a fast and cost-effective way presents an analytical and technological challenge. Here, an approach is presented where for the first time an allele-specific PCR (AS-PCR) is combined with a newly developed high fundamental frequency quartz crystal microbalance array as biosensor for the amplification and detection, respectively, of cancer point mutations. Increased sensitivity, compared to fluorescence detection of the AS-PCR amplicons, is achieved through energy dissipation measurement of acoustically "lossy" liposomes binding to surface-anchored dsDNA targets. The method, applied to the screening of BRAF V600E and KRAS G12D mutations in spiked-in samples, was shown to be able to detect 1 mutant copy of genomic DNA in an excess of 104 wild-type molecules, that is, with a mutant allele frequency (MAF) of 0.01%. Moreover, validation of tissue and plasma samples obtained from melanoma, colorectal, and lung cancer patients showed excellent agreement with Sanger sequencing and ddPCR; remarkably, the efficiency of this AS-PCR/acoustic methodology to detect mutations in real samples was demonstrated to be below 1% MAF. The combined high sensitivity and technology-readiness level of the methodology, together with the ability for multiple sample analysis (24 array biochip), cost-effectiveness, and compatibility with routine workflow, make this approach a promising tool for implementation in clinical oncology labs for tissue and liquid biopsy.

Feedback control of chaotic systems using multiple shooting shadowing and application to Kuramoto-Sivashinsky equation.

We propose an iterative method to evaluate the feedback control kernel of a chaotic system directly from the system's attractor. Such kernels are currently computed using standard linear optimal control theory, known as linear quadratic regulator theory. This is however applicable only to linear systems, which are obtained by linearizing the system governing equations around a target state. In the present paper, we employ the preconditioned multiple shooting shadowing (PMSS) algorithm to compute the kernel directly from the nonlinear dynamics, thereby bypassing the linear approximation. Using the adjoint version of the PMSS algorithm, we show that we can compute the kernel at any point of the domain in a single computation. The algorithm replaces the standard adjoint equation (that is ill-conditioned for chaotic systems) with a well-conditioned adjoint, producing reliable sensitivities which are used to evaluate the feedback matrix elements. We apply the idea to the Kuramoto-Sivashinsky equation. We compare the computed kernel with that produced by the standard linear quadratic regulator algorithm and note similarities and differences. Both kernels are stabilizing, have compact support and similar shape. We explain the shape using two-point spatial correlations that capture the streaky structure of the solution of the uncontrolled system.

Acoustic Methodology for Selecting Highly Dissipative Probes for Ultrasensitive DNA Detection.

The objective of this work is to present a methodology for the selection of nanoparticles such as liposomes to be used as acoustic probes for the detection of very low concentrations of DNA. Liposomes, applied in the past as mass amplifiers and detected through frequency measurement, are employed in the current work as probes for energy-dissipation enhancement. Because the dissipation signal is related to the structure of the sensed nanoentity, a systematic investigation of the geometrical features of the liposome/DNA complex was carried out. We introduce the parameter of dissipation capacity by which several sizes of liposome and DNA structures were compared with respect to their ability to dissipate acoustic energy at the level of a single molecule/particle. Optimized 200 nm liposomes anchored to a dsDNA chain led to an improvement of the limit of detection (LoD) by 3 orders of magnitude when compared to direct DNA detection, with the new LoD being 1.2 fmol (or 26 fg/µL or 2 pM). Dissipation monitoring was also shown to be 8 times more sensitive than the corresponding frequency response. The high versatility of this new methodology is demonstrated in the detection of genetic biomarkers down to 1-2 target copies in real samples such as blood. This study offers new prospects in acoustic detection with potential use in real-world diagnostics.

Uncertainty quantification of sensitivities of time-average quantities in chaotic systems.

We consider time-average quantities of chaotic systems and their sensitivity to system parameters. When the parameters are random variables with a prescribed probability density function, the sensitivities are also random. The central aim of the paper is to study and quantify the uncertainty of the sensitivities; this is useful to know in robust design applications. To this end, we couple the nonintrusive polynomial chaos expansion (PCE) with the multiple shooting shadowing (MSS) method, and apply the coupled method to two standard chaotic systems, the Lorenz system and the Kuramoto-Sivashinsky equation. The method leads to accurate results that match well with Monte Carlo simulations (even for low chaos orders, at least for the two systems examined), but it is costly. However, if we apply the concept of shadowing to the system trajectories evaluated at the quadrature integration points of PCE, then the resulting regularization can lead to significant computational savings. We call the new method shadowed PCE (sPCE).

Ultrafast, low-power, PCB manufacturable, continuous-flow microdevice for DNA amplification.

The design and fabrication of a continuous-flow µPCR device with very short amplification time and low power consumption are presented. Commercially available, 4-layer printed circuit board (PCB) substrates are employed, with in-house designed yet industrially manufactured embedded Cu micro-resistive heaters lying at very close distance from the microfluidic network, where DNA amplification takes place. The 1.9-m-long microchannel in combination with desirably high flow velocities (for fast amplification) challenged the robustness of the sealing that was overcome with the development of a novel bonding method rendering the microdevice robust even at extreme pressure drops (12 bars). The proposed fabrication methods are PCB compatible, allowing for mass and reliable production of the µPCR device in the established PCB industry. The µPCR chip was successfully validated during the amplification of two different DNA fragments (and with different target DNA copies) corresponding to the exon 20 of the BRCA1 gene, and to the plasmid pBR322, a commonly used cloning vector in E. coli. Successful DNA amplification was demonstrated at total reaction times down to 2 min, with a power consumption of 2.7 W, rendering the presented µPCR one of the fastest and lowest power-consuming devices, suitable for implementation in low-resource settings. Detailed numerical calculations of the DNA residence time distributions, within an acceptable temperature range for denaturation, annealing, and extension, performed for the first time in the literature, provide useful information regarding the actual on-chip PCR protocol and justify the maximum volumetric flow rate for successful DNA amplification. The calculations indicate that the shortest amplification time is achieved when the device is operated at its enzyme kinetic limit (i.e., extension rate). Graphical abstract.

3D-printed Point-of-Care Platform for Genetic Testing of Infectious Diseases Directly in Human Samples Using Acoustic Sensors and a Smartphone.

The objective of this work is to develop a methodology and associated platform for nucleic acid detection at the point-of-care (POC) that is sensitive, user-friendly, affordable, rapid, and robust. The heart of this system is an acoustic wave sensor, based on a Surface Acoustic Wave (SAW) or Quartz Crystal Microbalance (QCM) device, which is employed for the label-free detection of isothermally amplified target DNA. Nucleic acids amplification and detection is demonstrated inside three crude human samples, i.e., whole blood, saliva, and nasal swab, spiked in with 10-100 Salmonella cells. To qualify for POC applications, a portable platform was developed based on 3D printing, integrating inside a single box: (i) simple fluidics based on plastic tubing and a mini peristaltic pump, (ii) a heating plate combined with disposable reaction tubes for isothermal amplification; (iii) a mini antenna analyzer operated through a tablet; and (iv) an acoustic wave device housing unit. The simplicity of the method combined with smartphone operation and detection, rapid sample-to-answer analysis time (30 min), and high performance (detection limit 4 × 103 CFU/ml) in three of the most important human samples in diagnostics suggest that the methodology could become a tool of choice for nucleic acid detection at the POC. In addition, the low cost of the platform and assay holds promise for its adoption in resource limited areas. The acoustic detection method is shown to give similar results with a standard colorimetric assay carried out in saliva and nasal swab but can also be used to detect nucleic acids inside whole blood, where a colorimetric assay failed to perform.

Endocrine Disrupting Chemicals: An Occult Mediator of Metabolic Disease.

Endocrine disrupting chemicals (EDCs), a heterogeneous group of exogenous chemicals that can interfere with any aspect of endogenous hormones, represent an emerging global threat for human metabolism. There is now considerable evidence that the observed upsurge of metabolic disease cannot be fully attributed to increased caloric intake, physical inactivity, sleep deficit, and ageing. Among environmental factors implicated in the global deterioration of metabolic health, EDCs have drawn the biggest attention of scientific community, and not unjustifiably. EDCs unleash a coordinated attack toward multiple components of human metabolism, including crucial, metabolically-active organs such as hypothalamus, adipose tissue, pancreatic beta cells, skeletal muscle, and liver. Specifically, EDCs' impact during critical developmental windows can promote the disruption of individual or multiple systems involved in metabolism, via inducing epigenetic changes that can permanently alter the epigenome in the germline, enabling changes to be transmitted to the subsequent generations. The clear effect of this multifaceted attack is the manifestation of metabolic disease, clinically expressed as obesity, metabolic syndrome, diabetes mellitus, and non-alcoholic fatty liver disease. Although limitations of EDCs research do exist, there is no doubt that EDCs constitute a crucial parameter of the global deterioration of metabolic health we currently encounter.

Micro-nano-bio acoustic system for the detection of foodborne pathogens in real samples.

The fast and efficient detection of foodborne pathogens is a societal priority, given the large number of food-poisoning outbreaks, and a scientific and technological challenge, given the need to detect as little as 1 viable cell in 25 gr of food. Here, we present the first approach that achieves the above goal, thanks to the use of a micro/nano-technology and the detection capability of acoustic wave sensors. Starting from 1 Salmonella cell in 25 ml of milk, we employ immuno-magnetic beads to capture cells after only 3 h of pre-enrichment and subsequently demonstrate efficient DNA amplification using the Loop Mediated Isothermal Amplification method (LAMP) and acoustic detection in an integrated platform, within an additional ½ h. The demonstrated 4 h sample-to-analysis time comes as a huge improvement to the current need of few days to obtain the same result. In addition, the work presents the first reported Lab-on-Chip platform that comprises an acoustic device as the sensing element, exhibiting impressive analytical features, namely, an acoustic limit of detection of 2 cells/µl or 3 aM of the DNA target and ability to detect in a label-free manner dsDNA amplicons in impure samples. The use of food samples together with the incorporation of the necessary pre-enrichment step and ability for multiple analysis with an internal control, make the proposed methodology highly relevant to real-world applications. Moreover, the work suggests that acoustic wave devices can be used as an attractive alternative to electrochemical sensors in integrated platforms for applications in food safety and the point-of-care diagnostics.

Sample-to-answer acoustic detection of DNA in complex samples.

The present study demonstrates the sensitive and label-free acoustic detection of dsDNA amplicons produced from whole Salmonella Thyphimurium cells without employing any DNA extraction and/or purification step, in the presence of the lysed bacterial cells and in a hybridization-free assay. A sample-to-answer assay is also shown during DNA detection directly in milk.

Lack of Definite Association of Vitamin D Deficiency with Diabetic Neuropathy. Investigation in Greek and in Bangladeshi Patients.

AIM: Determination of the 25(OH) vitamin D levels in Greek-born and in Bangladeshi immigrant patients in Greece with diabetes with and without polyneuropathy. MATERIALS AND METHODS: The method for the detection and staging of polyneuropathy proposed by Dyck, 1988 was used. RESULTS: A total of 111 Bangladeshi immigrants and 101 Greek diabetic patients took part in the study. Vitamin D levels were significantly lower in Bangladeshi than in Greek diabetic patients, and were significantly lower in Greek patients with small-fiber neuropathy. In Bangladeshi patients, there was no statistically significant difference in the subgroup of patients with polyneuropathy in comparison to those without polyneuropathy. CONCLUSION: The association of vitamin D deficiency only with a small number of Greek patients with exclusively small-fiber neuropathy does not allow us to draw a definite conclusion on the role of vitamin D in the pathogenesis of diabetic neuropathy.

Plasma micro-nanotextured polymeric micromixer for DNA purification with high efficiency and dynamic range.

We present a polymeric microfluidic chip capable of purifying DNA through solid phase extraction. It is designed to be used as a module of an integrated Lab-on-chip platform for pathogen detection, but it can also be used as a stand-alone device. The microfluidic channels are oxygen plasma micro-nanotextured, i.e. randomly roughened in the micro-nano scale, a process creating high surface area as well as high density of carboxyl groups (COOH). The COOH groups together with a buffer that contains polyethylene glycol (PEG), NaCl and ethanol are able to bind DNA on the microchannel surface. The chip design incorporates a mixer so that sample and buffer can be efficiently mixed on chip under continuous flow. DNA is subsequently eluted in water. The chip is able to isolate DNA with high recovery efficiency (96± 11%) in an extremely large dynamic range of prepurified Salmonella DNA as well as from Salmonella cell lysates that correspond to a range of 5 to 1.9 × 108 cells (0.263 fg to 2 × 500 ng). The chip was evaluated via absorbance measurements, polymerase chain reaction (PCR), and gel electrophoresis.

On the Hydrodynamic Nature of DNA Acoustic Sensing.

In this work we provide strong experimental evidence for the hydrodynamic nature of the acoustic wave/biomolecule interaction at a solid/liquid interface. By using a wide range of DNAs of various sizes and by assuming DNA attachment as discrete particles through a neutravidin/biotin link, we prove experimentally that the acoustic ratio (dissipation/frequency) is directly related to the molecules' intrinsic viscosity [η]. The relationship of [η] to the size and shape of biomolecules is described in general and more specifically for linear dsDNA; equations are derived linking the measured acoustic ratio to the number of dsDNA base pairs for two acoustic sensors, the QCM and Love-wave devices operating at a frequency of 35 and 155 MHz, respectively. Single-stranded DNAs were also tested and shown to fit well to the equation derived for the double-stranded molecules while new insight is provided on their conformation on a surface. Other types of DNA are also shown to fit the proposed model. The current work establishes a new way of viewing acoustic sensor data and lays down the groundwork for a surface technique where quantitative information can be obtained at the nanometer scale regarding the shape and size, i.e., conformation of biomolecules at an interface.

Micro-Nano-Bio Diagnostic System for Food Pathogen Detection Revolutionizes Food Safety Management & Protects Consumers Health.

The development of integrated, fast and affordable platforms for pathogen detection is an emerging area where a multidisciplinary approach is necessary for designing microsystems employing miniaturized devices; these new technologies promise a significant advancement of the current state of analytical testing leading to improved healthcare. In this work, the development of a lab-on-chip microsystem platform for the genetic analysis of Salmonella in milk samples is presented. The heart of the platform is an acoustic detection biochip, integrated with a microfluidic module. This detection platform is combined with a micro-processor, which, alongside with magnetic beads technology and a DNA micro-amplification module, are responsible for performing sample pre-treatment, bacteria lysis, nucleic acid purification and amplification. Automated, multiscale manipulation of fluids in complex microchannel networks is combined with novel sensing principles developed by some of the partners. This system is expected to have a significant impact in food-pathogen detection by providing for the first time an integrated detection test for Salmonella screening in a very short time. Finally, thanks to the low cost and compact technologies involved, the proposed set-up is expected to provide a competitive analytical platform for direct application in field settings.

Bacteria Murmur: Application of an Acoustic Biosensor for Plant Pathogen Detection.

A multi-targeting protocol for the detection of three of the most important bacterial phytopathogens, based on their scientific and economic importance, was developed using an acoustic biosensor (the Quartz Crystal Microbalance) for DNA detection. Acoustic detection was based on a novel approach where DNA amplicons were monitored and discriminated based on their length rather than mass. Experiments were performed during real time monitoring of analyte binding and in a direct manner, i.e. without the use of labels for enhancing signal transduction. The proposed protocol improves time processing by circumventing gel electrophoresis and can be incorporated as a routine detection method in a diagnostic lab or an automated lab-on-a-chip system for plant pathogen diagnostics.

The detection of multiple DNA targets with a single probe using a conformation-sensitive acoustic sensor.

By using an acoustic wave methodology that allows direct sensing of biomolecular conformations, we achieved the detection of multiple target DNAs using a single probe, exploiting the fact that each bound target results in a hybridized product of a different shape.

Diabetic neuropathy: comparison between Bangladeshi immigrants and Greek-born subjects.

The aim of this study was to compare Bangladeshi immigrants with diabetes to native Greeks with diabetes and to distinguish the different risk factors for polyneuropathy (PN) in the two ethnic groups. Subjects were recruited from the outpatient diabetic clinic of a general hospital. A total of 111 Bangladeshi immigrants (97 men and 14 women of mean age 47 years) and 101 native Greeks (82 men and 19 women of mean age 49 years) were included in the study. Sex, mean age, age at diabetes diagnosis, and diabetes duration did not differ between the two groups. PN was diagnosed in 53 (48%) Bangladeshi and in 59 (58%) Greek patients (p = 0.12). Large fiber neuropathy was less prevalent among Bangladeshis (18%) than in Greeks (53%) (p < 0.01). Small fiber neuropathy on the contrary were more frequent in Bangladeshis (18% vs. 7%) (p < 0.02). Regarding the risk factors for PN, Greek patients were taller, with higher BMI, and smoked more cigarettes (p < 0.001). They were also treated with more anti-lipid and antihypertensive agents. The higher percentage of SFN in Bangladeshi was mainly a result of the significantly greater incidence of erectile dysfunction (ED) in their group (68 Bangladeshi vs. 38 Greek men). It is well known that there are many causes of ED aside from SFN which were not evaluated in this study. Thus this conclusion should be taken with caution.

Comparative analysis of a-priori and a-posteriori dietary patterns using state-of-the-art classification algorithms: a case/case-control study.

OBJECTIVE: To compare the accuracy of a-priori and a-posteriori dietary patterns in the prediction of acute coronary syndrome (ACS) and ischemic stroke. This is actually the first study to employ state-of-the-art classification methods for this purpose. METHODS AND MATERIALS: During 2009-2010, 1000 participants were enrolled; 250 consecutive patients with a first ACS and 250 controls (60±12 years, 83% males), as well as 250 consecutive patients with a first stroke and 250 controls (75±9 years, 56% males). The controls were population-based and age-sex matched to the patients. The a-priori dietary patterns were derived from the validated MedDietScore, whereas the a-posteriori ones were extracted from principal components analysis. Both approaches were modeled using six classification algorithms: multiple logistic regression (MLR), naïve Bayes, decision trees, repeated incremental pruning to produce error reduction (RIPPER), artificial neural networks and support vector machines. The classification accuracy of the resulting models was evaluated using the C-statistic. RESULTS: For the ACS prediction, the C-statistic varied from 0.587 (RIPPER) to 0.807 (MLR) for the a-priori analysis, while for the a-posteriori one, it fluctuated between 0.583 (RIPPER) and 0.827 (MLR). For the stroke prediction, the C-statistic varied from 0.637 (RIPPER) to 0.767 (MLR) for the a-priori analysis, and from 0.617 (decision tree) to 0.780 (MLR) for the a-posteriori. CONCLUSION: Both dietary pattern approaches achieved equivalent classification accuracy over most classification algorithms. The choice, therefore, depends on the application at hand.

Familial mesothelioma in first degree relatives.

Occupational asbestos exposure is believed to be the primary etiologic link to mesothelioma. However, in the evaluation of familial mesothelioma, it is important to consider the possibility of household exposure to asbestos. In this study, we report a family in which the father with prolonged occupational asbestos exposure developed malignant pleural mesothelioma and his daughter 14 years later mesothelioma in situ with focally early invasion. Several reports of familial aggregations of mesothelioma strongly support that genetic factors in collaboration with environmental exposure may contribute etiologically to an as yet unknown fraction of occurrence of this disease.