Parallel Samples Research Articles

A mini-panel PET scanner-based microfluidic radiobioassay system allowing high-throughput imaging of real-time cellular pharmacokinetics

On-chip radiometric detection of biological samples using radiotracers has become an emerging research field known as microfluidic radiobioassays. Performing parallel radiobioassays is highly desirable for saving time/effort, reducing experimental variation between assays, and minimizing the cost of the radioisotope. Continuously infused microfluidic radioassay (CIMR) is one of the useful tools for investigating cellular pharmacokinetics and assessing the binding and uptakes of radiopharmaceuticals. However, existing CIMR systems can only measure the dynamics of one sample at a time due to the limited field of view (FOV) of the positron detector. To increase the throughput, we propose a new CIMR system with a custom-built miniaturized panel-based positron-emission tomography (PET) scanner and a parallel infusion setup/method, capable of imaging the cellular pharmacokinetics of three samples in one measurement. With this system, the pharmacokinetics of parallel or comparison samples can be imaged simultaneously. The increased throughput is attributed to two innovations: 1) the large 3D FOV of the mini-panel PET scanner, enabling more samples to be imaged in the microfluidic chip; and 2) a parallel infusion method, in which only one reference chamber is needed for indicating the dynamic input of the infused radiotracer medium, thus saving the total reference chambers needed compared to the current sequential infusion method. Combining the CIMR technique and the mini-panel PET scanner, this study also firstly demonstrated the feasibility of using PET, as an imaging modality, for microfluidic radiobioassays. Besides the increased throughput, the 3D imaging of PET also provides possibilities for further applications such as organoid/3D culturing systems, non-planar microfluidics, and organs-on-chips. The system is more practical for a broader range of applications in nuclear medicine, molecular imaging, and lab-on-a-chip studies.

Time Difference Penalized Traffic Signal Timing by LSTM Q-Network to Balance Safety and Capacity at Intersections

The conflict between limited road resources and rapid car ownership makes the traffic signal timing become a pivotal challenge. Emerging studies have been carried out on adaptive signal timing, but most of them still focus on the throughput of intersections, leaving safety and travel experience unconsidered. This paper proposes a time difference penalized traffic signal timing method by reinforcement learning technique to balance safety and throughput capacity in traffic control system. Firstly, a microcosmic state representation is proposed to integrate the dynamics of both traffic lights and road vehicles, including driver behaviors of lane changing, car-following, previous phase of traffic light and its duration. Secondly, an action space, including 8 signal phases, and a behavior-aware reward function are designed to resist the red-light overflow. Finally, a partial long short term memory (LSTM) network is trained to balance traffic efficiency and traveling experience. In the network training, a parallel sampling method is adopted to obtain experience from multiple environments to accelerate the training convergence in practical application. Experimental results show that the proposed method improves the intersection efficiency up to 14.28% compared to the fixed signal timing and 5.26% compared to DQN while getting rid of red-light overflow time.

Parallel MCMC sampling of AR-HMMs for prediction based option trading

In this paper we propose stochastic time series prediction by autoregressive Hidden Markov Models (AR-HMM). The model parameter estimation, hence the prediction, is carried out by Markov chain Monte Carlo (MCMC) sampling instead of finding a single m

Sample Tracking Using Unique Sequence Controls

Sample tracking and identity are essential when processing multiple samples in parallel. Sequencing applications often involve high sample numbers, and the data are frequently used in a clinical setting. As such, a simple and accurate intrinsic sample tracking process through a sequencing pipeline is essential. Various solutions have been implemented to verify sample identity, including variant detection at the start and end of the pipeline using arrays or genotyping, bioinformatic comparisons, and optical barcoding of samples. None of these approaches are optimal. To establish a more effective approach using genetic barcoding, we developed a panel of unique DNA sequences cloned into a common vector. A unique DNA sequence is added to the sample when it is first received and can be detected by PCR and/or sequencing at any stage of the process. The control sequences are approximately 200 bases long with low identity to any sequence in the National Center for Biotechnology Information nonredundant database (<30 bases) and contain no long homopolymer (>7) stretches. When a spiked next-generation sequencing library is sequenced, sequence reads derived from this control sequence are generated along with the standard sequencing run and are used to confirm sample identity and determine cross-contamination levels. This approach is used in our targeted clinical diagnostic whole-genome and RNA-sequencing pipelines and is an inexpensive, flexible, and platform-agnostic solution.

Approximation of Metro Water District Basin Using Parallel Computing of Emulator Based Spatial Optimization (PCESO)

Metro Water District (MWD) is an agency that administers water distribution in a large geographic region. It targets for existing conditions with future projections of water resources for conservation, supply, and usage. Hence, it is required to show proper water resources management for MWD. Where the river basin profiles are projected to provide the water resources management with potential issues for MWD. Here, Upper Chattahoochee River (UCR) basin of the Metropolitan North Georgia Water Planning District (MNGWPD) selected for the study area. UCR is one of the largest river basins in the MNGWPD and it provides drinking and primary receiving water for nearly 3.5 million people of Atlanta Metro Region. In this study, Parallel Computing of Emulator based Spatial Optimization (PCESO) framework developed for spatial optimization of large complex watersheds. The proposed framework optimizes the hydrological model by parallel computing, emulator fit, sampling design, and spatial optimization. The results showed that 1) the computational time required for spatial optimization was significantly reduced by 50%, 2) goodness-of-fit reached its threshold limit in all stations inclusive in reservoir containing stations, 3) the water balance components and the optimized parameter values with sensitivity index provided the physical phenomena of the study area and showed the approximate hydrological processes in MWD. Further, this proposed work incorporates into future climate data can provide an accurate hydrological analysis with water allocation issues like water use, demand, conservation, and supply for MWD and it helps to identify the water-related disasters floods and droughts.

Calibration and validation of a microporous polyethylene passive sampler for quantitative estimation of illicit drug and pharmaceutical and personal care product (PPCP) concentrations in wastewater influent

Wastewater-based epidemiology (WBE), the per capita normalised measurement of drugs, chemicals or metabolites in wastewater influent, relies on sampling and quantitative analysis to evaluate temporal and spatial trends of chemical consumption. Continuous, high-resolution, flow proportional composite sampling is optimal for accurate representations of chemical mass loads, but is rarely implemented, with conventional autosamplers providing relatively low frequency time or volume proportional samples. However, due to equipment or resource constraints at many wastewater treatment plants (WWTPs), even this may not be feasible. Passive sampling may provide an alternative sampling strategy. To investigate this, samplers comprising hollow, cylindrical Microporous Polyethylene Tubes (MPTs) containing polymeric sorbent phases of Strata-X and Strata-X in agarose were simultaneously deployed in a municipal WWTP influent stream. Samplers were extracted, analysed and evaluated for a range of illicit drugs and pharmaceuticals and personal care products (PPCPs) after 4, 7, 15, 21, and 29 day deployments. The MPT samplers were calibrated against 24-hour time proportional composite grab samples that were collected in parallel. Diffusion through the MPT governed uptake, reducing or eliminating the influence of external flow rates that may fluctuate unpredictably in a WWTP environment. Calibration data for six illicit drugs and fourteen PPCPs, including methamphetamine, benzoylecgonine, MDMA, codeine and carbamazepine, demonstrated linear accumulation in the samplers (R2 ≥ 0.84). Derived sampling rates for these analytes ranged from 0.25 to 17 mL d−1 for ibuprofen and verapamil, respectively. A validation study using this sampling rate data showed the MPT could effectively quantify concentrations (≥0.1 ng mL−1) of a range of amphetamine-type stimulants, opioids and metabolites as well as nicotine, accounting for 95% of the variance in parallel composite grab sample concentrations of these compounds. The MPT sampler shows promise for providing essential monitoring data for WBE, informing future intervention and research strategies.

Seeking for optimum culture medium for chlorella pyrenoidosa and analysis of the amino acid component

Chlorella Pyrenoidosa is one of the widely used algae in aquaculture. In order to find out a proper culture medium for high-density culturing to meet the demand of fish reproduction and water quality control, five normal algae culture media were test via multiple comparisons. The densities of the five groups, with six parallel samples each, which were cultured in corresponding medium, were determined by blood counting chamber on the beginning (0d), the 3rd day (3d), the 6th day (6d) and 9th day (9d). Then the growth curves were described and the growth radio were calculated and compared by One-Way ANOVA (Turkey method) using the SPSS 21.0 software. The multiple comparisons results revealed that HGZ group could reproduced a rapid and stable speed at high density, while SE group and Aquatic 4# reproduced faster than the HGZ group. Amino acid component results revealed that C. Pyrenoidosa contains 18 kinds of amino acid (42.19 ∼ 43.14% of the body mass). There are significant differences on total amino acid, fish essential amino acid and non-essential amino acid between groups based on the multiple comparisons. However, the amino acid could not meet the demand of fish or shellfish. Thus, extra amino acid, such as tryptophan and methionine should be added and the HGZ medium was the best choice for producing C. Pyrenoidosa to satisfy the aquaculture.

Determining surface phase diagrams including anharmonic effects

We introduce a massively parallel replica-exchange grand-canonical sampling algorithm to simulate materials at realistic conditions, in particular surfaces and clusters in reactive atmospheres. Its purpose is to determine in an automated fashion equilibrium phase diagrams for a given potential-energy surface (PES) and for any observable sampled in the grand-canonical ensemble. The approach enables an unbiased sampling of the phase space and is embarrassingly parallel. It is demonstrated for a model of Lennard-Jones system describing a surface in contact with a gas phase. Furthermore, the algorithm is applied to Si$_M$ clusters ($M=2, 4$) in contact with an H$_{2}$ atmosphere, with all interactions described at the \textit{ab initio} level, i.e., via density-functional theory, with the PBE gradient-corrected exchange-correlation functional. We identify the most thermodynamically stable phases at finite $T, p$(H$_{2}$) conditions.

Variations in Greenhouse Gas Fluxes in Response to Short-Term Changes in Weather Variables at Three Elevation Ranges, Wakiso District, Uganda

Weather conditions are among the major factors leading to the increasing greenhouse gas (GHG) fluxes from the agricultural soils. In this study, variations in the soil GHG fluxes with precipitation and soil temperatures at different elevation ranges in banana–coffee farms, in the Wakiso District, Uganda, were evaluated. The soil GHG fluxes were collected weekly, using the chamber method, and analyzed by using gas chromatography. Parallel soil temperature samples were collected by using a REOTEMP soil thermometer. Daily precipitation was measured with an automated weather station instrument installed on-site. The results showed that CO2, N2O, and CH4 fluxes were significantly different between the sites at different elevation ranges. Daily precipitation and soil temperatures significantly (p &lt; 0.05) affected the soil GHG fluxes. Along an elevation gradient, daily precipitation and soil temperatures positively associated with the soil GHG fluxes. The combined factors of daily precipitation and soil temperatures also influence the soil GHG fluxes, but their effect was less than that of the single effects. Overall, daily precipitation and soil temperatures are key weather factors driving the soil GHG fluxes in time and space. This particular study suggests that agriculture at lower elevation levels would help reduce the magnitudes of the soil GHG fluxes. However, this study did not measure the soil GHG fluxes from the non-cultivated ecosystems. Therefore, future studies should focus on assessing the variations in the soil GHG fluxes from non-cultivated ecosystems relative to agriculture systems, at varying elevation ranges.

A Decoupled Automation Platform for Hydrogen/Deuterium Exchange Mass Spectrometry Experiments.

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) is a biophysical technique well suited to the characterization of protein dynamics and protein-ligand interactions. In order to accurately define the rate of exchange, HDX experiments require the repeated measure of deuterium incorporation into the target protein across a range of time points. Accordingly, the HDX-MS experiment is well suited to automation, and a number of automated systems for HDX-MS have been developed. The most widely utilized platforms all operate an integrated design, where robotic liquid handling is interfaced directly with a mass spectrometer. With integrated designs, the exchange samples are prepared and injected into the LC-MS following a "real-time" serial workflow. Here we describe a new HDX-MS platform that is comprised of two complementary pieces of automation that disconnect the sample preparation from the LC-MS analysis. For preparation, a plate-based automation system is used to prepare samples in parallel, followed by immediate freezing and storage. A second piece of automation has been constructed to perform the thawing and LC-MS analysis of frozen samples in a serial mode and has been optimized to maximize the duty cycle of the mass spectrometer. The decoupled configuration described here reduces experiment time, significantly improves capacity, and improves the flexibility of the platform when compared with a fully integrated system.

Assessing pollution of aquatic environments with diatoms’ DNA metabarcoding: experience and developments from France water framework directive networks

Ecological status assessment of watercourses is based on the calculation of quality indices using pollution sensitivity of targeted biological groups, including diatoms. The determination and quantification of diatom species is generally based on microscopic morphological identification, which requires expertise and is time-consuming and costly. In Europe, this morphological approach is legally imposed by standards and regulatory decrees by the Water Framework Directive (WFD). Over the past decade, a DNA-based molecular biology approach has newly been developed to identify species based on genetic criteria rather than morphological ones (i.e. DNA metabarcoding). In combination with high throughput sequencing technologies, metabarcoding makes it possible both to identify all species present in an environmental sample and to process several hundred samples in parallel. This article presents the results of two recent studies carried out on the WFD networks of rivers of Mayotte (2013–2018) and metropolitan France (2016–2018). These studies aimed at testing the potential application of metabarcoding for biomonitoring in the context of the WFD. We discuss the various methodological developments and optimisations that have been made to make the taxonomic inventories of diatoms produced by metabarcoding more reliable, particularly in terms of species quantification. We present the results of the application of this DNA approach on more than 500 river sites, comparing them with those obtained using the standardised morphological method. Finally, we discuss the potential of metabarcoding for routine application, its limits of application and propose some recommendations for future implementation in WFD.

Planning High-Quality Motions for Concentric Tube Robots in Point Clouds via Parallel Sampling and Optimization.

We present a method that plans motions for a concentric tube robot to automatically reach surgical targets inside the body while avoiding obstacles, where the patient's anatomy is represented by point clouds. Point clouds can be generated intra-operatively via endoscopic instruments, enabling the system to update obstacle representations over time as the patient anatomy changes during surgery. Our new motion planning method uses a combination of sampling-based motion planning methods and local optimization to efficiently handle point cloud data and quickly compute high quality plans. The local optimization step uses an interior point optimization method, ensuring that the computed plan is feasible and avoids obstacles at every iteration. This enables the motion planner to run in an anytime fashion, i.e., the method can be stopped at any time and the best solution found up until that point is returned. We demonstrate the method's efficacy in three anatomical scenarios, including two generated from endoscopic videos of real patient anatomy.

Algorithms for estimating the partition function of restricted Boltzmann machines

Accurate estimates of the normalization constants (partition functions) of energy-based probabilistic models (Markov random fields) are highly important, for example, for assessing the performance of models, monitoring training progress, and conducting likelihood ratio tests. Several algorithms for estimating the partition function (in relation to a reference distribution) have been introduced, including Annealed Importance Sampling (AIS) and Bennett's Acceptance Ratio method (BAR). However, their conceptual similarities and differences have not been worked out so far and systematic comparisons of their behavior in practice have been missing. We devise a unifying theoretical framework for these algorithms, which comprises existing variants and suggests new approaches. It is based on a generalized form of Crooks' equality linking the expectation over a distribution of samples generated by a transition operator to the expectation over the distribution induced by the reversed operator. The framework covers different ways of generating samples, such as parallel tempering and path sampling. An empirical comparison revealed the differences between the methods when estimating the partition function of restricted Boltzmann machines and Ising models. In our experiments, BAR using parallel tempering worked well with a small number of bridging distributions, while path sampling based AIS performed best when many bridging distributions were available. Because BAR gave the overall best results, we favor it over AIS. Furthermore, the experiments showed the importance of choosing a proper reference distribution.

Afamin expression in breast cancer

Breast cancer is a collection of molecularly and clinically distinct neoplastic disease. Recent research has shown the information regarding gene expression in breast cancer could be beneficial in the designing of an optimal treatment plan and may also provide with prognostic information. The creation of tissue microarrays (TMA) allows for the rapid immunohistochemical analysis of thousands of tissue samples in parallel with minimal damage to the original blocks. This study was designed with the application of tissue microarray (TMA) to analyze the afamin status in breast cancer with the hope of elucidating the possible relationship between afamin expressions and breast cancer. Archival tissue specimens from 106 patients with primary invasive breast cancer were analyzed for afamin expression by immunhistochemical staining with TMA. Results were compared to clinicopathologic data by multivariate analysis. TNM stage has shown significant relationship to the overall 5-year survival rate. However, afamin expression was not significantly related to overall five-year survival. Immunohistochemical staining with TMA was convenient and feasible for analyzing afamin expression status in breast cancer. Our preliminary results show that afamin expression showed no significant prognostic value in breast cancer.

Re-evaluation of DNA based identification results of victims of a terrorist attack 25 years later

In July 1994 there was a second terrorist attack against a Jewish institution in Buenos Aires city. It targeted the Argentine Israelite Mutual Association (AMIA) and the bomb toppled its building, killed 85 and hurt over 300 people. The Supreme Court ordered DFPS/SHDG to carry out the identification of the fragmented remains by means of DNA analysis. At that time five VNTRs, seven STRs including five autosomal, one X, and one on the Y chromosome, mtDNA sequencing (HVR I and II) and MVR were used. The techniques used were all manual, southern blot and polyacrylamide gels with radioactive probes or primer detection. The first report was presented on November 7, 1994. In addition to the molecular data, identifications were made using conventional forensic criteria: dactyloscopy, radiography, dentistry and personal traits. In July 2016, the AMIA Investigative Investigation Unit wanted to clarify the identity of additional victims and asked the DFPS/SHDG and as a second opinion laboratory the Argentine team of Forensic Anthropology (EAAF), to analyze samples in parallel, compare them to the results reported in 1994, and perform additional tests on samples not previously analyzed by DNA typing.Both laboratories used automated platforms (ABI 3500); commercial kits Powerplex Fusion, Identifiler and mtDNA sequencing. Although TH01 and vWA are the only tested STR markers in 1994 that are still in use, most results reported in 1994 were confirmed by both laboratories. Additionally, it was possible to identify a victim whose material had initially been analyzed but, given its state of degradation, it had not been possible to obtain a genetic profile. The use of more sensitive megaplexes made it possible to identify a missing person 23 years later.The overall results demonstrate the robustness of the DNA analyses and the great increase in the sensitivity of the new analytical systems used and underscore the importance of including a second opinion lab to warrant the quality of the results.

Profiling of Circulating Free DNA Using Targeted and Genome-wide Sequencing in Patients with SCLC

IntroductionSCLC accounts for approximately 250,000 deaths worldwide each year. Acquisition of adequate tumor biopsy samples is challenging, and liquid biopsies present an alternative option for patient stratification and response monitoring.MethodsWe applied whole genome next-generation sequencing to circulating free DNA (cfDNA) from 39 patients with limited-stage (LS) SCLC and 30 patients with extensive-stage SCLC to establish genome-wide copy number aberrations and also performed targeted mutation analysis of 110 SCLC associated genes. Quantitative metrics were calculated for copy number aberrations, including percent genome amplified (PGA [the percentage of genomic regions amplified]), Z-score (a measure of standard deviation), and Moran’s I (a measure of spatial autocorrelation). In addition CellSearch, an epitope-dependent enrichment platform, was used to enumerate circulating tumor cells (CTCs) from a parallel blood sample.ResultsGenome-wide and targeted cfDNA sequencing data identified tumor-related changes in 94% of patients with LS SCLC and 100% of patients with extensive-stage SCLC. Parallel analysis of CTCs based on at least 1 CTC/7.5 mL of blood increased tumor detection frequencies to 95% for LS SCLC. Both CTC counts and cfDNA readouts correlated with disease stage and overall survival.ConclusionsWe demonstrate that a simple cfDNA genome-wide copy number approach provides an effective means of monitoring patients through treatment and show that targeted cfDNA sequencing identifies potential therapeutic targets in more than 50% of patients. We are now incorporating this approach into additional studies and trials of targeted therapies.

Perinatal Bisphenol A Exposure and Reprogramming of Imprinted Gene Expression in the Adult Mouse Brain.

Genomic imprinting, a phenomenon by which genes are expressed in a monoallelic, parent-of-origin-dependent fashion, is critical for normal brain development. Expression of imprinted genes is regulated via epigenetic mechanisms, including DNA methylation (5-methylcytosine, 5mC), and disruptions in imprinting can lead to disease. Early-life exposure to the endocrine disrupting chemical bisphenol A (BPA) is associated with abnormalities in brain development and behavior, as well as with disruptions in epigenetic patterning, including 5mC and DNA hydroxymethylation (5-hydroxymethylcytosine, 5hmC). Using an established mouse model of perinatal environmental exposure, the objective of this study was to examine the effects of perinatal BPA exposure on epigenetic regulation of imprinted gene expression in adult mice. Two weeks prior to mating, dams were assigned to control chow or chow containing an environmentally relevant dose (50 µg/kg) of BPA. Exposure continued until offspring were weaned at post-natal day 21, and animals were followed until 10 months of age. Expression of three imprinted genes—Pde10a, Ppp1r9a, and Kcnq1, as well as three genes encoding proteins critical for regulation of 5mC and 5hmC—Dnmt1, Tet1, and Tet2, were evaluated in the right cortex and midbrain using qRT-PCR. Perinatal BPA exposure was associated with a significant increase in adult Kcnq1 (p = 0.04) and Dnmt1 (p = 0.02) expression in the right cortex, as well as increased expression of Tet2 in the midbrain (p = 0.03). Expression of Tet2 and Kcnq1 were positively correlated in the midbrain. Analysis of 5mC and 5hmC at the Kcnq1 locus was conducted in parallel samples using standard and oxidative bisulfite conversion followed by pyrosequencing. This analysis revealed enrichment of both 5mC and 5hmC at this locus in both brain regions. No significant changes in 5mC and 5hmC at Kcnq1 were observed with perinatal BPA exposure. Together, these data suggest that perinatal BPA exposure results in altered expression of Kcnq1, Dnmt1, and Tet2 in the adult mouse brain. Further studies with larger sample sizes are necessary to understand the mechanistic basis for these changes, as well as to determine the implications they have for brain development and function.

Rapid and sensitive detection of interleukin-6 in serum via time-resolved lateral flow immunoassay

Interleukin 6 (IL-6) is an interleukin that acts as both a proinflammatory and anti-inflammatory cytokine. It can be used as a potential diagnostic biomarker for sepsis. The aim of this study was to establish an easy-to-use detection kit for rapid, quantitative and on-site detection of IL-6. To develop the new IL-6 quantitative detecting kit, a double-antibody sandwich immunofluorescent assay was employed based on europium nanoparticles (Eu-np) combined with lateral flow immunoassay (LFIA). The performance of the new developed kit was evaluated in the aspects of parallel analysis, linearity, sensitivity, precision, accuracy, specificity and clinical sample analysis. Two-hundred and fourteen serum samples were used to carry out the clinical sample analysis. The new IL-6 quantitative detecting kit exhibited a wide linear range (2–500 pg/mL) and a good sensitivity (0.37 pg/mL). The intra-assay coefficient of variation (CV) and the inter-assay CV were 5.92%–8.87% and 7.59%–9.04%, respectively. The recovery rates ranged from 102% to 106%. Furthermore, a high correlation (n = 214, r = 0.9756, p < 0.01) was obtained when compared with SIEMENS CLIA IL-6 kit. Thus, the new quantitative method for detecting IL-6 has been successfully established. The results indicated that the newly-developed strip based on Eu-np combined with LFIA was a facile, fast, highly sensitive, low-cost, reliable biosensor and suitable for rapid and point-of-care test (POCT) for IL-6 in serum.

Feasibility of Localized Metabolomics in the Study of Pancreatic Islets and Diabetes.

(1) Background: Disruption of insulin production by native or transplanted pancreatic islets caused by auto/allo-immunity leads to hyperglycemia, a serious health condition and important therapeutic challenge due to the lifelong need for exogeneous insulin administration. Early metabolic biomarkers can prompt timely interventions to preserve islet function, but reliable biomarkers are currently lacking. We explored the feasibility of “localized metabolomics” where initial biomarker discovery is made in aqueous humor samples for further validation in the circulation. (2) Methods: We conducted non-targeted metabolomic studies in parallel aqueous humor and plasma samples from diabetic and nondiabetic mice. Metabolite levels and associated pathways were compared in both compartments as well as to an earlier longitudinal dataset in hyperglycemia-progressor versus non-progressor non-obese diabetic (NOD) mice. (3) Results: We confirmed that aqueous humor samples can be used to assess metabolite levels. About half of the identified metabolites had well-correlated levels in the aqueous humor and plasma. Several plasma metabolites were significantly different between diabetic and nondiabetic animals and between males and females, and many of them were correlated with the aqueous humor. (4) Conclusions: This study provides proof-of-concept evidence that aqueous humor samples enriched with islet-related metabolites and representative of the immediate islet microenvironment following intraocular islet transplant can be used to assess metabolic changes that could otherwise be overlooked in the general circulation. The findings support localized metabolomics, with and without intraocular islet transplant, to identify biomarkers associated with diabetes and islet allograft rejection.

Rotorcraft virtual sensors via deep regression

Raw sensor data containing high-fidelity information is highly desirable for valuable post-processing. We developed a machine learning model that performs deep regression to infer rotorcraft component vibration spectra from a few flight conditional indicators (CI). The model consists of a deep neural network of fully connected layers (DNN) that performs high-dimensional and non-linear multivariate regression to reconstruct raw accelerometer data. The network architecture hyperparameters were optimized using an evolutionary genetic algorithm (GA) that was more effective than random and manual search methods. The best GA design was further tuned to achieve spectrum reconstruction accuracies above 95% on validation datasets. An automated model generator workflow was developed to train and evaluate thousands of DNN designs using parallel asynchronous execution on a Cray XC50, which were monitored and studied. Finally, as a verification step of the DNN inference model operation and performance, a detailed sensitivity analysis was performed using a modified Sobol sampling technique to understand response behavior and limitations. The sensitivity analysis method utilized Dask-distributed across multiple nodes on our HPC to evaluate millions of generated samples in parallel.